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1
Mouadeb, Abdu-Nasser R. "Extension of linear quadratic regulator theory and its applications." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/7535.
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Linear Quadratic Regulatory theory (L.Q.R.) has received widespread application due to its simplicity and also due to the fact that the control provided this by theory is linear in form. These features make the implication of feedback control and easy task. In contrast, nonlinear regulation lack those attractive features enjoyed by the linear regulator. Moreover, in order to obtain the feedback control, one has to solve Hamilton-Jacobi-Bellman equation which is not an easy task. Also, if solution can be obtained, implementation is not always practical. In this work, we extend the Linear Quadratic Regulatory theory to the following; (I) LQR theory is modified for the case when there is no control contribution to the cost functional. (II) LQR is used to regulate or fine-tune a nonlinear system around a nominal trajectory through linearization of nonlinear systems. (III) Applying the LQR theory for the regulation of angular velocities of a three-axes satellite around a nominal point. (IV) Applying the LQR for the regulation of the movement of a robot around a time-optional trajectory. (V) The limitation of the control obtained through linearization is indicated.
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Benner, Peter, and Jens Saak. "Linear-Quadratic Regulator Design for Optimal Cooling of Steel Profiles." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200601597.
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We present a linear-quadratic regulator (LQR) design for a heat transfer model describing the cooling process of steel profiles in a rolling mill. Primarily we consider a feedback control approach for a linearization of the nonlinear model given there, but we will also present first ideas how to use local (in time) linearizations to treat the nonlinear equation with a regulator approach. Numerical results based on a spatial finite element discretization and a numerical algorithm for solving large-scale algebraic Riccati equations are presented both for the linear and nonlinear models.
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Khalid, Muhammad Salman. "Linear Quadratic Regulator and Receding Horizon Control for Constrained Systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515489.
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Aravinthan, Abhiramy. "Linear quadratic regulator design for doubly fed induction generator using singular perturbation techniques." Thesis, Wichita State University, 2012. http://hdl.handle.net/10057/5523.
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Doubly fed induction generators (DFIG) are widely used in wind power generation because of their ability to be operated at varying rotational speeds while producing power output at a constant frequency. Electrical dynamics of a DFIG is modeled using field oriented control and represented as fourth order system. This fourth order dynamics exposes a two-time scale behavior. Using singular perturbation techniques the time scales can be separated as slow and fast subsystems. Feedback control schemes can be designed and the closed-loop stability of each model can be compared. In this work, a linear quadratic feedback controller is designed for the DFIG electrical dynamics using exact, reduced order and composite models. The performances of the closed loop models are compared based on the system cost. The robustness and reliability of the control schemes are analyzed for each controller designs based on the nominal system. Based on the analysis and results, the reduced order controller performance is equally as good as the exact and composite designs during steady state operations.Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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Nelson, Karen E. (Karen Elizabeth) M. Eng Massachusetts Institute of Technology. "Active control of tensegrity structures and its applications using Linear Quadratic Regulator algorithms." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66845.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 61-62).
The concept of responsive architecture has inspired the idea structures which are adaptable and change in order to better fit the user. This idea can be extended to structural engineering with the implementing of structures which change to better take on their external loading. The following text explores the utilization of active control for tensegrity systems in order to achieve an adaptable structure. To start, a background of the physical characteristics of these structures is given along with the methods which are used to find their form. Next, the different methods which have been previously used to achieve active control in tensegrity are reviewed as well as the objectives they intended to achieve. From there, the Linear Quadratic Regulator (LQR) algorithm is introduced as a possible method to be used in designing active control. A planar tensegrity beam is described, whose form was found by the force density method. A simulation is then conducted, which applies the LQR algorithm to this structure for the purposes of active control. This simulation served both to demonstrate the force density and LQR methods, as well as to study how different control parameters and actuator placements effects the efficiency of the control. This text concludes with a discussion of the results of this simulation.
by Karen E. Nelson.
M.Eng.
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Uddin, Md Mosleh. "Active Vibration Control of Helicopter Rotor Blade by Using a Linear Quadratic Regulator." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/td/2499.
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Active vibration control is a widely implemented method for the helicopter vibration control. Due to the significant progress in microelectronics, this technique outperforms the traditional passive control technique due to weight penalty and lack of adaptability for the changing flight conditions. In this thesis, an optimal controller is designed to attenuate the rotor blade vibration. The mathematical model of the triply coupled vibration of the rotating cantilever beam is used to develop the state-space model of an isolated rotor blade. The required natural frequencies are determined by the modified Galerkin method and only the principal aerodynamic forces acting on the structure are considered to obtain the elements of the input matrix. A linear quadratic regulator is designed to achieve the vibration reduction at the optimum level and the controller is tuned for the hovering and forward flight with different advance ratios.
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Bushong, Philip Merton. "A multi-loop guidance scheme using singular perturbation and linear quadratic regulator techniques simultaneously." Diss., This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-07282008-135643/.
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Vugrin, Eric D. "On Approximation and Optimal Control of Nonnormal Distributed Parameter Systems." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11149.
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For more than 100 years, the Navier-Stokes equations and various linearizations have been used as a model to study fluid dynamics. Recently, attention has been directed toward studying the nonnormality of linearized problems and developing convergent numerical schemes for simulation of these sytems. Numerical schemes for optimal control problems often require additional properties that may not be necessary for simulation; these properties can be critical when studying nonnormal problems. This research is concerned with approximating infinite dimensional optimal control problems with nonnormal system operators.
We examine three different finite element methods for a specific convection-diffusion equation and prove convergence of the infinitesimal generators. Additionally, for two of these schemes, we prove convergence of the associated feedback gains. We apply these three schemes to control problems and compare the performance of all three methods.Ph. D.
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Bagheri, Shahriar. "Modeling, Simulation and Control System Design for Civil Unmanned Aerial Vehicle (UAV)." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-96458.
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Unmanned aerial systems have been widely used for variety of civilian applications over the past few years. Some of these applications require accurate guidance and control. Consequently, Unmanned Aerial Vehicle (UAV) guidance and control attracted many researchers in both control theory and aerospace engineering. Flying wings, as a particular type of UAV, are considered to have one of the most efficient aerodynamic structures. It is however difficult to design robust controller for such systems. This is due to the fact that flying wings are highly sensitive to control inputs. The focus of this thesis is on modeling and control design for a UAV system. The platform understudy is a flying wing developed by SmartPlanes Co. located in Skellefteå, Sweden. This UAV is particularly used for topological mapping and aerial photography. The novel approach suggested in this thesis is to use two controllers in sequence. More precisely, Linear Quadratic Regulator (LQR) is suggested to provide robust stability, and Proportional, Integral, Derivative (PID) controller is suggested to provide reference signal regulation. The idea behind this approach is that with LQR in the loop, the system becomes more stable and less sensitive to control signals. Thus, PID controller has an easier task to do, and is only used to provide the required transient response. The closed-loop system containing the developed controller and a UAV non-linear dynamic model was simulated in Simulink. Simulated controller was then tested for stability and robustness with respect to some parametric uncertainty. Obtained results revealed that the LQR successfully managed to provide robust stability, and PID provided reference signal regulation.
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Alvarez, Genesis Barbie. "Control Design for a Microgrid in Normal and Resiliency Modes of a Distribution System." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/94627.
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As inverter-based distributed energy resources (DERs) such as photovoltaic (PV) and battery energy storage system (BESS) penetrate within the distribution system. New challenges regarding how to utilize these devices to improve power quality arises. Before, PV systems were required to disconnect from the grid during a large disturbance, but now smart inverters are required to have dynamically controlled functions that allows them to remain connected to the grid. Monitoring power flow at the point of common coupling is one of the many functions the controller should perform. Smart inverters can inject active power to pick up critical load or inject reactive power to regulate voltage within the electric grid. In this context, this thesis focuses on a high level and local control design that incorporates DERs. Different controllers are implemented to stabilize the microgrid in an Islanding and resiliency mode. The microgrid can be used as a resiliency source when the distribution is unavailable. An average model in the D-Q frame is calculated to analyze the inherent dynamics of the current controller for the point of common coupling (PCC). The space vector approach is applied to design the voltage and frequency controller. Secondly, using inverters for Volt/VAR control (VVC) can provide a faster response for voltage regulation than traditional voltage regulation devices. Another objective of this research is to demonstrate how smart inverters and capacitor banks in the system can be used to eliminate the voltage deviation. A mixed-integer quadratic problem (MIQP) is formulated to determine the amount of reactive power that should be injected or absorbed at the appropriate nodes by inverter. The Big M method is used to address the nonconvex problem. This contribution can be used by distribution operators to minimize the voltage deviation in the system.Master of Science
Reliable power supply from the electric grid is an essential part of modern life. This critical infrastructure can be vulnerable to cascading failures or natural disasters. A solution to improve power systems resilience can be through microgrids. A microgrid is a small network of interconnected loads and distributed energy resources (DERs) such as microturbines, wind power, solar power, or traditional internal combustion engines. A microgrid can operate being connected or disconnected from the grid. This research emphases on the potentially use of a Microgrid as a resiliency source during grid restoration to pick up critical load. In this research, controllers are designed to pick up critical loads (i.e hospitals, street lights and military bases) from the distribution system in case the electric grid is unavailable. This case study includes the design of a Microgrid and it is being tested for its feasibility in an actual integration with the electric grid. Once the grid is restored the synchronization between the microgrid and electric must be conducted. Synchronization is a crucial task. An abnormal synchronization can cause a disturbance in the system, damage equipment, and overall lead to additional system outages. This thesis develops various controllers to conduct proper synchronization. Interconnecting inverter-based distributed energy resources (DERs) such as photovoltaic and battery storage within the distribution system can use the electronic devices to improve power quality. This research focuses on using these devices to improve the voltage profile within the distribution system and the frequency within the Microgrid.
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Krueger, Denise A. "Stabilized Finite Element Methods for Feedback Control of Convection Diffusion Equations." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11214.
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We study the behavior of numerical stabilization schemes in the context of linear quadratic regulator (LQR) control problems for convection diffusion equations. The motivation for this effort comes from the observation that when linearization is applied to fluid flow control problems the resulting equations have the form of a convection diffusion equation. This effort is focused on the specific problem of computing the feedback functional gains that are the kernels of the feedback operators defined by solutions of operator Riccati equations. We develop a stabilization scheme based on the Galerkin Least Squares (GLS) method and compare this scheme to the standard Galerkin finite element method. We use cubic B-splines in order to keep the higher order terms that occur in GLS formulation. We conduct a careful numerical investigation into the convergence and accuracy of the functional gains computed using stabilization. We also conduct numerical studies of the role that the stabilization parameter plays in this convergence. Overall, we discovered that stabilization produces much better approximations to the functional gains on coarse meshes than the unstabilized method and that adjustments in the stabilization parameter greatly effects the accuracy and convergence rates. We discovered that the optimal stabilization parameter for simulation and steady state analysis is not necessarily optimal for solving the Riccati equation that defines the functional gains. Finally, we suggest that the stabilized GLS method might provide good initial values for iterative schemes on coarse meshes.Ph. D.
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Monte, Alegre Dário [UNESP]. "Metodologia dos observadores de estado para diagnose de falhas em sistemas contendo elementos finitos de placas de Kirchoff." Universidade Estadual Paulista (UNESP), 2009. http://hdl.handle.net/11449/94560.
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O presente trabalho apresenta a metodologia dos observadores de estado para a detecção e localização de falhas em sistemas contendo elementos finitos de placas de Kirchoff. Tal metodologia consiste na montagem de um banco de observadores de estado, o qual é capaz de detectar falhas presentes no sistema, além de localizar o componente danificado e a porcentagem de falha. As matrizes de ganho dos observadores de estado foram determinadas por dois métodos distintos: o método Regulador Quadrático Linear e das Desigualdades Matriciais Lineares. Nesse trabalho, foi utilizada uma placa plana fina montada sobre um sistema de suspensão similar ao de uma plataforma veicular, representando um veiculo simplificadamente. A modelagem da plataforma utilizada foi realizada mediante a utilização do método dos elementos finitos, considerando-se diferentes números de elemento no modelo. O tipo do elemento finito utilizado foi o elemento de placa de Kirchoff. Adicionalmente foi analisada a influência de elementos de controle junto à suspensão da plataforma no movimento da mesma. O modelo considerado, juntamente com os programas computacionais desenvolvidos, foram utilizados para a simulação do movimento da plataforma. Na literatura, normalmente são apresentadas simulações para o movimento de apenas ¼ do veículo, neste trabalho, no entanto, os programas desenvolvidos podem simular o movimento do veiculo inteiro. Foram realizadas simulações computacionais para o movimento da plataforma com a finalidade de se detectar e localizar falhas introduzidas nos elementos da suspensão e também foram realizados testes experimentais, com os mesmos fins. Mediante tais testes (teóricos e experimentais) verificou-se a eficácia da metodologia desenvolvida e a sua principal limitação: o número de elementos finitos considerado no modelo relacionado com o número de medidas efetuadas e a observabilidade do sistema.
This work presents the state observers methodology for the detection and location of faults in systems containing finite elements of plate of Kirchoff. This methodology consists in the assembly of a bank of state observers, which is capable of detecting faults in the system, and also to locate the damaged component and the percentage of failure. The gain matrices of the state observers were determined by two different methods, these are the method Linear Quadratic Regulator and the Linear Matrix Inequalities. In this work was considered a thin plate mounted on a suspension system that is similar to a vehicle platform, representing a vehicle in a simplified way. The modeling of the platform used was performed by using the finite element method, considering different numbers of element in the model. The finite element used was the Kirchoff’s plate element. It was also studied the influence of elements of control, together with the suspension of the platform, into its movement. The model considered, together with the developed computational programs, were used to simulate the movement of the platform. In the literature, usually are presented simulations for the movement of only ¼ of the vehicle, in this work, the developed programs can simulate the movement of the entire vehicle. It was realized computational simulations for the movement of the platform in order to detect and locate faults introduced in the elements of the suspension and experimental tests were also conducted with the same purpose. Through such tests (theoretical and experimental) it was verified the effectiveness of the developed methodology and its major limitation: the number of finite elements considered in the model related with the number of outputs and the observability of the system.
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Giesselmann, Jens Uwe Michael, and jens giesselmann@gmx net. "Development of an Active Magnetic Attitude Determination and Control System for Picosatellites on highly inclined circular Low Earth Orbits." RMIT University. Aerospace, Mechanical and Manufacturing Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070514.162516.
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Small satellites are becoming increasingly important to the aerospace industry mainly due to their significantly reduced development and launch cost as well as shorter development time frames. In order to meet the requirements imposed by critically limited resources of very small satellites, e.g. picosatellites, innovative approaches have to be taken in the design of effective subsystem technologies. This thesis presents the design of an active attitude determination and control system for flight testing on-board the picosatellite 'Compass-1' of the University of Applied Sciences Aachen, Germany. The spacecraft of the CubeSat class with a net spacecraft mass of only 1kg uses magnetic coils as the only means of actuation in order to satisfy operational requirements imposed by its imagery payload placed on a circular and polar Low Earth Orbit. The control system is capable of autonomously dissipating the tumbling rates of the spacecraft after launch interface separ ation and aligning the boresight of the payload into the desired nadir direction within a pointing error of approximately 10°. This nadir-pointing control is achieved by a full-state feedback Linear Quadratic Regulator which drives the attitude quaternion and their respective rates of change into the desired reference. The state of the spacecraft is determined by a static statistical QUEST attitude estimator processing readings of a three-axis magnetometer and a set of five sun sensors. Linear Floquet theory is applied to quantify the stability of the controller and a non-linear dynamics simulation is used to confirm that the attitude asymptotically converges to the reference in the absence of environmental disturbances. In the presence of disturbances the system under control suffers from fundamental underactuaction typical for purely magnetic attitude control but maintains satisfactory alignment accuracies within operational boundaries.
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SILVA, Márcio Eduardo Gonçalves. "Algoritmos da Família LMS para a Solução Aproximada da HJB em Projetos Online de Controle Ótimo Discreto Multivariável e Aprendizado por Reforço." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/1891.
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The technique of linear control based on the minimization of a quadratic performance index using the second method of Lyapunov to guarantee the stability of the system, if this is controllable and observable. however, this technique is inevitably necessary to find the solution of the HJB or Riccati equation. The control system design online need, real time, to adjust your feedback gain to maintain a certain dynamic, it requires the calculation of the Riccati equation solution in each sampling generating a large computational load that can derail its implementation. This work shows an intelligent control system design that meets the optimal or suboptimal control action from the sensory data of process states and the instantaneous cost observed after each state transition. To find this optimal control action or policy, the approximate dynamic programming and adaptive critics are used, based on the parameterizations given by the problem of linear quadratic regulator (LQR), but without explicitly solving the associated Riccati equation. More specifically, the LQR problem is solved by four different methods which are the Dynamic Programming Heuristic, the Dual Heuristic Dynamic Programming, Action Dependent Dynamic Programming Heuristic and Action Dependent Dual Heuristic Dynamic Programming algorithms. However, these algorithms depend on knowledge of the value functions to derive the optimal control actions. These value functions with known structures have their parameters estimated using the least mean square family and Recursive Least Squares algorithms. Two processes that have the Markov property were used in the computational validation of the algorithms adaptive critics implemented, one corresponds to the longitudinal dynamics of an aircraft and the other to an electrical circuit.
A técnica de controle linear baseado na minimização de um índices de desempenho quadrático utilizando o segundo método de Liapunov garante a estabilidade do sistema, se este for controlável e observável. Por outro lado, nessa técnica inexoravelmente é necessário encontrar a solução da Equação Hamilton-Jacobi-Bellman (HJB) ou Riccati. Em projeto de sistema de controle online que necessita, em tempo real, alterar seus ganhos de retroação para manter uma certa dinâmica, impõe o cálculo da solução da equação de Riccati em cada instante de amostragem gerando uma grande carga computacional que pode inviabilizar sua implementação. Neste trabalho, mostra-se o projeto de um sistema de controle inteligente que encontra a ação de controle ótima ou subótima a partir de dados sensoriais dos estados do processo e do custo instantâneo observados após cada transição de estado. Para encontrar essa ação de controle ou política ótima, a programação dinâmica aproximada ou críticos adaptativos são utilizados, tendo como base as parametrizações dado pelo problema do regulador linear quadrático (LQR), mas sem resolver explicitamente a equação de Riccati associada. Mais especificamente, o problema do LQR é resolvido por quatro métodos distintos que são os algoritmos de Programação Dinâmica Heurística, a Programação Dinâmica Heurística Dual, a Programação Dinâmica Heurística Dependente de Ação e a Programação Dinâmica Heurística Dual Dependente de Ação. Entretanto, esses algoritmos dependem do conhecimento das funções valor para, assim, derivar as ações de controle ótimas. Essas funções valor com estruturas conhecidas tem seus parâmetros estimados utilizando os algoritmos da família dos mínimos quadrados médios e o algoritmo de Mínimos Quadrados Recursivo. Dois processos que obedecem à propriedade de Markov foram empregados na validação computacional dos algoritmos críticos adaptativos, um corresponde à dinâmica longitudinal de uma aeronave e o outro à de um circuito elétrico.
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Ababnah, Ahmad A. "Sensor deployment in detection networks-a control theoretic approach." Diss., Kansas State University, 2010. http://hdl.handle.net/2097/6699.
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Doctor of PhilosophyDepartment of Electrical and Computer Engineering
Balasubramaniam Natarajan
For any automated surveillance operation to be successful, it is critical to have sensing resources strategically positioned to observe, interpret, react and maybe even predict events.In many practical scenarios, it is also expected that different zones within a surveillance area may have different probability of event detection (or false alarm) requirements. The operational objective in such surveillance systems is to optimize resources (number of sensors and the associated cost) and their deployment while guaranteeing a certain assured level of detection/false alarm performance. In this dissertation, we study two major challenges related to sensor deployment in distributed sensor networks (DSNs) for detection applications. The first problem we study is the sensor deployment problem in which we ask the following question: Given a finite number of sensors (with a known sensing profile), how can we deploy these sensors such that we best meet the detection and false alarm requirements in a DSN employing a specific information fusion rule? Even though sensor deployment has garnered significant interest in the past, a unified, analytical framework to model and study sensor deployment is lacking. Additionally, the algorithms proposed in literature are typically heuristic in nature and are limited to (1) simplistic DSN fusion architectures, and (2) DSNs with uniform detection/false alarm requirements. In this dissertation, we propose a novel treatment of the sensor deployment problem using concepts from optimal control theory. Specifically, the deployment problem is formulated as a linear quadratic regulator (LQR) problem which provides a rigorous and analytical framework to study the deployment problem. We develop new sensor deployment algorithms that are applicable to a wide range of DSN architectures employing different fusion rules such as (1) logical OR fusion; (2) value fusion; (3) majority decision fusion, and (4) optimal decision fusion. In all these cases, we demonstrate that our proposed control theoretic deployment approach is able to significantly outperform previously proposed algorithms. The second problem considered in this dissertation is the “self healing” problem in which we ask the following question: After the failure of a number of sensors, how can one reconfigure the DSN such that the performance degradation due to sensor loss is minimized? Prior efforts in tackling the self healing problem typically rely on assumptions that don’t accurately capture the behavior of practical sensors/networks and focus on minimizing performance degradation at a local area of the network instead of considering overall performance of the DSN. In this work, we propose two self healing strategies the first approach relies on adjusting decision thresholds at the fusion center. The second approach involves sensor redeployment based on our control theoretic deployment framework. Simulation results illustrate that the proposed algorithms are effective in alleviating the performance degradation due to sensor loss.
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Ortega, Felix Mauricio Escalante. "Filtragem e controle recursivos robustos aplicados em um pêndulo invertido." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-15092016-075814/.
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O estudo da estabilidade e desempenho em sistemas de controle é um tópico relevante na teoria de sistemas. Quando são assumidas incertezas no modelo da planta, existe uma maior dificuldade para garantir um nível de desempenho adequado do sistema dinâmico e a estabilidade pode ser comprometida. Neste trabalho são utilizados um regulador linear quadrático robusto e um filtro de Kalman robusto combinados em uma única formulação para tratar de sistemas dinâmicos incertos em tempo real. O caso de estudo selecionado é o pêndulo invertido. Seus principais desafios de controle encontrados na literatura: estabilização, seguimento e levantamento-captura, serão considerados. Os algoritmos utilizados são motivados pelo fato de que problemas estocásticos podem ser resolvidos por meio de argumentos determinísticos, baseados nos conceitos de função penalidade e mínimos quadrados regularizados. Desta forma, é possível a obtenção do melhor desempenho em contrapartida à máxima influência de incerteza admissível. A análise de desempenho do controlador robusto é realizada por meio de ensaios práticos incluindo incertezas na planta, ruído nos sensores e distúrbios no sinal de controle do pêndulo.The study of stability and performance in control systems is a relevant topic in systems theory. When uncertainties are considered in the model of the plant, there is a greater difficulty in ensuring an appropriate performance level of the dynamic system, plus, the stability could be compromised as well. In this dissertation a robust linear quadratic regulator and a robust Kalman filter are used in a unified manner to deal with uncertain dynamic systems in real time. The selected case study is the inverted pendulum. Its main control challenges found in the literature will be considered: stabilization, tracking and catching swing-up. The used algorithms are motivated by the fact that stochastic problems can be solved through deterministic arguments based on the concepts of penalty function and regularized least-squares. Thus, it is possible to obtain an optimal performance for the maximum acceptable uncertainty. The performance analysis of the robust control is carried out by practical experiments including uncertainties in the plant, noise in the sensors and disturbance in the pendulum control signal.
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Brito, Filho Joaquim Gomes. "CONTROLE ROBUSTO LQG/LTR COM RECUPERAÇÃO DO GANHO DA MALHA DE TRANSFERÊNCIA." Universidade Federal do Maranhão, 2006. http://tedebc.ufma.br:8080/jspui/handle/tede/392.
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Previous issue date: 2006-05-31In this work is presented a method to solve the Eigenstructure Allocation pro- blem for multivariable dynamic systems by means of Robust Controllers Design Linear Quadratic Gaussian, LQG/LTR Loop transfer Recovery and Hierarchical Genetic Algorithm in three levels. It shows an uni¯ed method for controllers ro- bust design that are one systematical of the three stages of LQG/LTR methodo- logy. The evolutionary computation is used in the primary level that is the gain controller optimal determination to guarantee the terms of robust stability. The intermediary level, consists in the utilization of a AG to determine the Kalman state observer gain. The last level of this hierarchy consists of recovery the ro- bustness properties of the LQR design which were lost due to inclusion of the LQG loop by means of a GA. The method is veri¯ed in a dynamic system which represents an aircraft in cruzeiro speed, a LQG/LQR-hierarchic design perfor- mance analysis in the frequency domain and of time show the commitments that should be taken over in applications of the real world systems.
Apresenta-se um método para resolver o problema de Alocação de Auto-estrutura para sistemas dinâmicos multivariáveis por meio do Projeto de Controladores Ro- busto Gaussiano Linear Quadrático, Recuperação da Malha de Transferência e Algoritmo Genético Hierárquico em três níveis. Mostra-se um método unificado para o projeto de controladores robustos que são uma sistematização das três etapas da metodologia LQG/LTR. A computação evolutiva é utilizada no nível primário que é a determinação dos ganhos do controlador ótimo para garantir as condições de estabilidade robusta. O nível intermediário, consiste na utilização de um AG para determinar os ganhos de Kalman do observador de estado. O último nível desta hierarquia consiste da recuperação das propriedades de ro- bustez do projeto LQR que foram perdidas devido a inclusão da malha LQG por meio de um AG. O método é verficado em um sistema dinâmico que re- presenta uma aeronave em velocidade cruzeiro, uma análise de desempenho do projeto LQG/LQR-hierárquico no domínio da frequência e do tempo mostram os compromissos que devem ser assumidos em aplicações de sistemas do mundo real.
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Kaplan, Ceren. "Leo Satellites: Attitude Determination And Control Components." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607189/index.pdf.
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In this thesis, application of linear control methods to control the attitude of a Low-Earth Orbit satellite is studied. Attitude control subsystem is first introduced by explaining attitude determination and control components in detail. Satellite dynamic equations are derived and linearized for controller design. Linear controller and linear quadratic regulator are chosen as controllers for attitude control. The actuators used for control are reaction wheels and magnetic torquers. MATLAB-SIMULINK program is used in order to simulate satellite dynamical model (actual nonlinear model) and controller model. In simulations, the satellite parameters are selected to be similar to the actual BILSAT-1 satellite parameters. In conclusion, simulations obtained from different linear control methods are compared within themselves and with nonlinear control methods, at the same time with that obtained from BILSAT-1 satellite log data.
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Vick, Tyler J. "Geometry Modeling and Adaptive Control of Air-Breathing Hypersonic Vehicles." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1397468045.
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Monte, Alegre Dário. "Metodologia dos observadores de estado para diagnose de falhas em sistemas contendo elementos finitos de placas de Kirchoff /." Ilha Solteira : [s.n.], 2009. http://hdl.handle.net/11449/94560.
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Orientador: Gilberto Pechoto de MeloBanca: Luiz de Paula do Nascimento
Banca: Silmara Cassola
Resumo: O presente trabalho apresenta a metodologia dos observadores de estado para a detecção e localização de falhas em sistemas contendo elementos finitos de placas de Kirchoff. Tal metodologia consiste na montagem de um banco de observadores de estado, o qual é capaz de detectar falhas presentes no sistema, além de localizar o componente danificado e a porcentagem de falha. As matrizes de ganho dos observadores de estado foram determinadas por dois métodos distintos: o método Regulador Quadrático Linear e das Desigualdades Matriciais Lineares. Nesse trabalho, foi utilizada uma placa plana fina montada sobre um sistema de suspensão similar ao de uma plataforma veicular, representando um veiculo simplificadamente. A modelagem da plataforma utilizada foi realizada mediante a utilização do método dos elementos finitos, considerando-se diferentes números de elemento no modelo. O tipo do elemento finito utilizado foi o elemento de placa de Kirchoff. Adicionalmente foi analisada a influência de elementos de controle junto à suspensão da plataforma no movimento da mesma. O modelo considerado, juntamente com os programas computacionais desenvolvidos, foram utilizados para a simulação do movimento da plataforma. Na literatura, normalmente são apresentadas simulações para o movimento de apenas ¼ do veículo, neste trabalho, no entanto, os programas desenvolvidos podem simular o movimento do veiculo inteiro. Foram realizadas simulações computacionais para o movimento da plataforma com a finalidade de se detectar e localizar falhas introduzidas nos elementos da suspensão e também foram realizados testes experimentais, com os mesmos fins. Mediante tais testes (teóricos e experimentais) verificou-se a eficácia da metodologia desenvolvida e a sua principal limitação: o número de elementos finitos considerado no modelo relacionado com o número de medidas efetuadas e a observabilidade do sistema.
Abstract: This work presents the state observers methodology for the detection and location of faults in systems containing finite elements of plate of Kirchoff. This methodology consists in the assembly of a bank of state observers, which is capable of detecting faults in the system, and also to locate the damaged component and the percentage of failure. The gain matrices of the state observers were determined by two different methods, these are the method Linear Quadratic Regulator and the Linear Matrix Inequalities. In this work was considered a thin plate mounted on a suspension system that is similar to a vehicle platform, representing a vehicle in a simplified way. The modeling of the platform used was performed by using the finite element method, considering different numbers of element in the model. The finite element used was the Kirchoff's plate element. It was also studied the influence of elements of control, together with the suspension of the platform, into its movement. The model considered, together with the developed computational programs, were used to simulate the movement of the platform. In the literature, usually are presented simulations for the movement of only ¼ of the vehicle, in this work, the developed programs can simulate the movement of the entire vehicle. It was realized computational simulations for the movement of the platform in order to detect and locate faults introduced in the elements of the suspension and experimental tests were also conducted with the same purpose. Through such tests (theoretical and experimental) it was verified the effectiveness of the developed methodology and its major limitation: the number of finite elements considered in the model related with the number of outputs and the observability of the system.
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Mattei, Rafael Daia. "Detecção de danos em sistemas mecânicos via observadores de estado de ordem plena em paralelo /." Ilha Solteira, 2019. http://hdl.handle.net/11449/181663.
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Orientador: Gilberto Pechoto de MeloResumo: As metodologias de monitoramento da integridade estrutural baseadas em observadores de estado, em sua grande maioria, utilizam o resíduo obtido a partir da diferença entre a medida e a estimativa de dada resposta dinâmica do sistema para o processo de detecção de danos. Contudo, em determinadas situações, tem-se interesse em realizar o monitoramento através de certa resposta dinâmica que não pode ser medida diretamente. Desta forma, a principal contribuição deste trabalho é propor uma metodologia de detecção de danos para sistemas mecânicos, cujo resíduo é obtido a partir da diferença entre as estimativas do comportamento dinâmico de determinada região do sistema. Estas estimativas são geradas por dois observadores de estado de ordem plena em paralelo, ambos projetados a partir do modelo físico-matemático do sistema em monitoramento sem danos, cujos os ganhos ótimos são determinados pelo método LQR, do inglês Linear Quadratic Regulator. A diferença entre os observadores consiste em serem baseados em conjuntos de medidas distintos. Simulações computacionais são apresentadas para demonstrar a aplicação desta metodologia, de maneira que são discutidas as vantagens e desvantagens em monitorar o sistema utilizando diferentes tipos de força de excitação. Os resultados obtidos são satisfatórios para a detecção dos tipos de dano considerados neste trabalho.
Abstract: Structural health monitoring methodologies based on state observers, for the most part, use the residual obtained from the di erence between the measurement and the estimate of the given dynamic response of the system to the damage detection process. However, in certain situations, it is interesting to carry out the monitoring through a certain dynamic response that can not be measured directly. In this way, the main contribution of this work is to propose a methodology of damage detection for mechanical systems, whose residue is obtained from the di erence between the estimates of the dynamic behavior of a certain region of the system. These estimates are generated by two parallel full-order state observers, both designed from the physical-mathematical model of the monitoring system without damages, whose optimal gains are determined by the LQR (Linear Quadratic Regulator) method. The di erence between observers is that they are based on di erent sets of measures. Computational simulations are presented to demonstrate the application of this methodology, so that the advantages and disadvantages of monitoring the system using di erent types of excitation force are discussed. The results obtained are satisfactory for the detection of the types of damage considered in this work.
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Murari, André Luiz de Lacerda Ferreira. "Regulador quadrático linear ponderado com otimização por enxame de partículas modificado aplicado a geradores de indução com rotor bobinado." reponame:Repositório Institucional da UFABC, 2018.
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Orientador: Prof. Dr. Alfeu Joãzinho Sguarezi FilhoCoorientador: Prof. Dr. José Alberto Torrico Altuna
Tese (doutorado) - Universidade Federal do ABC. Programa de Pós-Graduação em Energia, Santo André, 2018.
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McDowell, Journey. "Comparison of Modern Controls and Reinforcement Learning for Robust Control of Autonomously Backing Up Tractor-Trailers to Loading Docks." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2100.
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Two controller performances are assessed for generalization in the path following task of autonomously backing up a tractor-trailer. Starting from random locations and orientations, paths are generated to loading docks with arbitrary pose using Dubins Curves. The combination vehicles can be varied in wheelbase, hitch length, weight distributions, and tire cornering stiffness. The closed form calculation of the gains for the Linear Quadratic Regulator (LQR) rely heavily on having an accurate model of the plant. However, real-world applications cannot expect to have an updated model for each new trailer. Finding alternative robust controllers when the trailer model is changed was the motivation of this research.
Reinforcement learning, with neural networks as their function approximators, can allow for generalized control from its learned experience that is characterized by a scalar reward value. The Linear Quadratic Regulator and the Deep Deterministic Policy Gradient (DDPG) are compared for robust control when the trailer is changed. This investigation quantifies the capabilities and limitations of both controllers in simulation using a kinematic model. The controllers are evaluated for generalization by altering the kinematic model trailer wheelbase, hitch length, and velocity from the nominal case.
In order to close the gap from simulation and reality, the control methods are also assessed with sensor noise and various controller frequencies. The root mean squared and maximum errors from the path are used as metrics, including the number of times the controllers cause the vehicle to jackknife or reach the goal. Considering the runs where the LQR did not cause the trailer to jackknife, the LQR tended to have slightly better precision. DDPG, however, controlled the trailer successfully on the paths where the LQR jackknifed. Reinforcement learning was found to sacrifice a short term reward, such as precision, to maximize the future expected reward like reaching the loading dock. The reinforcement learning agent learned a policy that imposed nonlinear constraints such that it never jackknifed, even when it wasn't the trailer it trained on.
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Farrell, Michael David. "Error-State Estimation and Control for a Multirotor UAV Landing on a Moving Vehicle." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/7879.
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Though multirotor unmanned aerial vehicles (UAVs) have become widely used during the past decade, challenges in autonomy have prevented their widespread use when moving vehicles act as their base stations. Emerging use cases, including maritime surveillance, package delivery and convoy support, require UAVs to autonomously operate in this scenario. This thesis presents improved solutions to both the state estimation and control problems that must be solved to enable robust, autonomous landing of multirotor UAVs onto moving vehicles.Current state-of-the-art UAV landing systems depend on the detection of visual fiducial markers placed on the landing target vehicle. However, in challenging conditions, such as poor lighting, occlusion, or extreme motion, these fiducial markers may be undected for significant periods of time. This thesis demonstrates a state estimation algorithm that tracks and estimates the locations of unknown visual features on the target vehicle. Experimental results show that this method significantly improves the estimation of the state of the target vehicle while the fiducial marker is not detected.This thesis also describes an improved control scheme that enables a multirotor UAV to accurately track a time-dependent trajectory. Rooted in Lie theory, this controller computes the optimal control signal based on an error-state formulation of the UAV dynamics. Simulation and hardware experiments of this control scheme show its accuracy and computational efficiency, making it a viable solution for use in a robust landing system.
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Prešinský, Ján. "Návrh a rozbor LQ-regulátoru pro podélný a stranový pohyb letadla." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-232106.
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This diploma thesis is focused on designing and specifying a linear quadratic regulator for longitudinal and lateral motion of the aircraft. The regulator is designed for a linear system obtained from a linearization of our nonlinear dynamic dynamic model of aircraft around the basic reference state (trimmed state-and-level ight). To nd a complete description of this reference state, some optimality problem has to be solved and the solution of this problem is called a trimmed state.
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Erdogan, Zeynep. "Development Of A Control Strategy For Road Vehicles With Semi-active Suspensions Using A Full Vehicle Ride Model." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610392/index.pdf.
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The main motivation of this study is the design of a control strategy for semi-active vehicle suspension systems to improve ride comfort for road vehicles. In order to achieve this objective, firstly the damping characteristics of Magnetorheological dampers will be reviewed. Then an appropriate semi-active control strategy manipulating the inputs of the dampers to create suitable damping forces will be designed. Linear Quadratic Regulator (LQR) control strategy is the primary focus area on semi-active control throughout this study. Further, skyhook controllers are examined and compared with optimal LQR controllers. The semi-active controller is tuned using a linearized full (4 wheel) vehicle ride model with seven degrees of freedom. Some selected simulations are carried out by using a nonlinear model to tune LQR controller in an effort to optimize bounce, pitch, and roll motion of the vehicle. Time domain simulations and frequency response analysis are used to justify the effectiveness of the proposed LQR control strategy.
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Johansson, Stefan. "Tools for Control System Design : Stratification of Matrix Pairs and Periodic Riccati Differential Equation Solvers." Doctoral thesis, Umeå, 2009. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=9789172647336.
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RÊGO, Patricia Helena Moraes Rêgo. "Convergência de Algoritmo Genético Hierárquico para Recuperação da Malha LQR por Controladores LQG/LTR." Universidade Federal do Maranhão, 2007. http://tedebc.ufma.br:8080/jspui/handle/tede/1852.
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FAPEMA
In this work are proposed models and a convergence analysis of a hierarchical genetic algorithm for the linear quadratic regulator design loop recovery through LQG/LTR controllers. Models are oriented to the weighting and covariance matrices searching of the performance indices of the LQR and LQG design, respectively, and to the selection of the matrices for the LQR design loop recovery gain. The convergence analysis aims at promoting the enhancement of the algorithm performance, as well as to generate satisfactory solutions and speed up the convergence time. The algorithm performance is evaluated with respect to the e ects of an elitist strategy embodied into the algorithm and to variations in the values of some given parameters of the algorithm. The proposed methodology is evaluated in a multi-variable dynamical system representing an aircraft.
Propõe-se neste trabalho os modelos e a análise de convergência de um algoritmo genético hierárquico para recuperação da malha de projeto do regulador linear quadrático por controladores LQG/LTR (Linear Quadratic Gaussian/Loop Transfer Recovery). Os modelos dedicam-se à busca das matrizes de ponderações e covariâncias dos índices de desempenho dos projetos de controladores LQR (Linear Quadratic Regulator) e LQG (Linear Quadratic Gaussian), respectivamente, e à seleção de matrizes de ajuste para o ganho de recuperação da malha do projeto LQR. O objetivo da análise de convergência é promover melhorias no desempenho do algoritmo no sentido de gerar soluções satisfatórias e acelerar o tempo de convergência. O desempenho do algoritmo é avaliado em relação aos efeitos de uma estratégia elitista incorporada ao algoritmo e à variações nos valores de determinados parâmetros do algoritmo. A metodologia proposta é avaliada em um sistema dinâmico multivariável que representa uma aeronave.
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SILVA, Fabio Nogueira da. "Métodos neuronais para a solução da equação algébrica de Riccati e o LQR." Universidade Federal do Maranhão, 2008. http://tedebc.ufma.br:8080/jspui/handle/tede/1817.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ)
Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão (FAPEMA)
We present in this work the results about two neural networks methods to solve the algebraic Riccati(ARE), what are used in many applications, mainly in the Linear Quadratic Regulator (LQR), H2 and H1 controls. First is showed the real symmetric form of the ARE and two methods based on neural computation. One feedforward neural network (FNN), that de¯nes an error as function of the ARE and a recurrent neural network (RNN), which converts a constrain optimization problem, restricted to the state space model, into an unconstrained convex optimization problem de¯ning an energy as function of the ARE and Cholesky factor. A proposal to chose the learning parameters of the RNN used to solve the ARE, by making a surface of the parameters variations, thus we can tune the neural network for a better performance. Computational experiments related with the plant matrices perturbations of the tested systems in order to perform an analysis of the behavior of the presented methodologies, that are based on homotopies methods, where we chose a good initial condition and compare the results to the Schur method. Two 6th order systems were used, a Doubly Fed Induction Generator(DFIG) and an aircraft plant. The results showed the RNN a good alternative compared with the FNN and Schur methods.
Apresenta-se nesta dissertação os resultados a respeito de dois métodos neuronais para a resolução da equação algébrica de Riccati(EAR), que tem varias aplicações, sendo principalmente usada pelos Regulador Linear Quadrático(LQR), controle H2 e controle H1. É apresentado a EAR real e simétrica e dois métodos baseados em uma rede neuronal direta (RND) que tem a função de erro associada a EAR e uma rede neuronal recorrente (RNR) que converte um problema de otimização restrita ao modelo de espaço de estados em outro de otimização convexa em função da EAR e do fator de Cholesky de modo a usufruir das propriedades de convexidade e condições de otimalidade. Uma proposta para a escolha dos parâmetros da RNR usada para solucionar a EAR por meio da geração de superfícies com a variação paramétrica da RNR, podendo assim melhor sintonizar a rede neuronal para um melhor desempenho. Experimentos computacionais relacionados a perturbações nos sistemas foram realizados para analisar o comportamento das metodologias apresentadas, tendo como base o princípio dos métodos homotópicos, com uma boa condição inicial, a partir de uma ponto de operação estável e comparamos os resultados com o método de Schur. Foram usadas as plantas de dois sistemas: uma representando a dinâmica de uma aeronave e outra de um motor de indução eólico duplamente alimentado(DFIG), ambos sistemas de 6a ordem. Os resultados mostram que a RNR é uma boa alternativa se comparado com a RND e com o método de Schur.
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Beteto, Marco Antonio Leite. "Less conservative conditions for the robust and Gain-Scheduled LQR-state derivative controllers design /." Ilha Solteira, 2019. http://hdl.handle.net/11449/180976.
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Orientador: Edvaldo AssunçãoResumo: Neste trabalho é proposta a resolução do problema do regulador linear quadrático (Linear Quadratic Regulator - LQR) via desigualdades matriciais lineares (Linear Matrix Inequalities - LMIs) para sistemas lineares e invariantes no tempo sujeitos a incertezas politópicas, bem como para sistemas lineares sujeitos a parâmetros variantes no tempo (Linear Parameter Varying - LPV). O projeto dos controladores é baseado na realimentação derivativa. A escolha da realimentação derivativa se dá devido à sua fácil implementação em certas aplicações como, por exemplo, no controle de vibrações. Os sinais usados na realimentação são aceleração e velocidade, sendo obtidos por meio de acelerômetros. Por meio do método proposto é possível obter condições LMIs para a síntese de controladores que garantam a estabilização do sistema em malha fechada, sendo que os controladores possuem desempenho otimizado. Para a formulação das condições LMIs, uma função de Lyapunov do tipo quadrática é utilizada. Exemplos teóricos e simulações são utilizados como forma de validação dos métodos propostos, além de mostrar que os novos resultados apresentam condições menos conservadoras. Além disso, ao final é apresentada uma implementação prática em um sistema de suspensão ativa, produzida pela Quanser®.
Abstract: The resolution of linear quadratic regulator (LQR) problem via linear matrix inequalities (LMIs) for linear time-invariant systems subject to polytopic uncertainties, as linear systems subjects to linear parameter varying (LPV), is proposed in this work. The controllers' designs are based on the state derivative feedback. The aim to the choice of the state derivative feedback is your easy implementation in a class of mechanical systems, such as in vibration control, for example. The signals used for feedback are acceleration and velocity, it is obtained by means of accelerometers. Through the proposed method it is possible to obtain LMIs conditions for the synthesis of controllers that guarantee the stabilisation of the closed-loop system, being that the controllers have optimised performance. For the LMIs conditions formulations, a Lyapunov function of type quadratic is used. As a form of validation, theoretical examples and simulations are performed, besides to show that the new results are less conservative. Furthermore, a practical implementation in an active suspension system, produced by Quanser®, is performed.
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Silva, Fabio Nogueira da. "Métodos Neuronais para a Solução da Equação Algébrica de Riccati e o LQR." Universidade Federal do Maranhão, 2008. http://tedebc.ufma.br:8080/jspui/handle/tede/401.
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Previous issue date: 2008-06-20FUNDAÇÃO DE AMPARO À PESQUISA E AO DESENVOLVIMENTO CIENTIFICO E TECNOLÓGICO DO MARANHÃO
We present in this work the results about two neural networks methods to solve the algebraic Riccati(ARE), what are used in many applications, mainly in the Linear Quadratic Regulator (LQR), H2 and H1 controls. First is showed the real symmetric form of the ARE and two methods based on neural computation. One feedforward neural network (FNN), that de¯nes an error as function of the ARE and a recurrent neural network (RNN), which converts a constrain optimization problem, restricted to the state space model, into an unconstrained convex optimization problem de¯ning an energy as function of the ARE and Cholesky factor. A proposal to chose the learning parameters of the RNN used to solve the ARE, by making a surface of the parameters variations, thus we can tune the neural network for a better performance. Computational experiments related with the plant matrices perturbations of the tested systems in order to perform an analysis of the behavior of the presented methodologies, that are based on homotopies methods, where we chose a good initial condition and compare the results to the Schur method. Two 6th order systems were used, a Doubly Fed Induction Generator(DFIG) and an aircraft plant. The results showed the RNN a good alternative compared with the FNN and Schur methods.
Apresenta-se nesta dissertação os resultados a respeito de dois métodos neuronais para a resolução da equação algébrica de Riccati(EAR), que tem varias aplicações, sendo principalmente usada pelos Regulador Linear Quadrático(LQR), controle H2 e controle H1. É apresentado a EAR real e simétrica e dois métodos baseados em uma rede neuronal direta (RND) que tem a função de erro associada a EAR e uma rede neuronal recorrente (RNR) que converte um problema de otimização restrita ao modelo de espaço de estados em outro de otimização convexa em função da EAR e do fator de Cholesky de modo a usufruir das propriedades de convexidade e condições de otimalidade. Uma proposta para a escolha dos parâmetros da RNR usada para solucionar a EAR por meio da geração de superfícies com a variação paramétrica da RNR, podendo assim melhor sintonizar a rede neuronal para um melhor desempenho. Experimentos computacionais relacionados a perturbações nos sistemas foram realizados para analisar o comportamento das metodologias apresentadas, tendo como base o princípio dos métodos homotópicos, com uma boa condição inicial, a partir de uma ponto de operação estável e comparamos os resultados com o método de Schur. Foram usadas as plantas de dois sistemas: uma representando a dinâmica de uma aeronave e outra de um motor de indução eólico duplamente alimentado(DFIG), ambos sistemas de 6a ordem. Os resultados mostram que a RNR é uma boa alternativa se comparado com a RND e com o método de Schur.
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Mohammadzadeh, Soroush. "System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/868.
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"Maintaining an efficient and reliable infrastructure requires continuous monitoring and control. In order to accomplish these tasks, algorithms are needed to process large sets of data and for modeling based on these processed data sets. For this reason, computationally efficient and accurate modeling algorithms along with data compression techniques and optimal yet practical control methods are in demand. These tools can help model structures and improve their performance. In this thesis, these two aspects are addressed separately. A principal component analysis based adaptive neuro-fuzzy inference system is proposed for fast and accurate modeling of time-dependent behavior of a structure integrated with a smart damper. Since a smart damper can only dissipate energy from structures, a challenge is to evaluate the dissipativity of optimal control methods for smart dampers to decide if the optimal controller can be realized using the smart damper. Therefore, a generalized deterministic definition for dissipativity is proposed and a commonly used controller, LQR is proved to be dissipative. Examples are provided to illustrate the effectiveness of the proposed modeling algorithm and evaluating the dissipativity of LQR control method. These examples illustrate the effectiveness of the proposed modeling algorithm and dissipativity of LQR controller."
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Aasa, Johan. "Linear-Quadratic Regulation of ComputerRoom Air Conditioners." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-71031.
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Data centers operations are notoriously energy-hungry, with the computing and cooling infrastructures drawing comparable amount of electrical power to operate. A direction to improve their efciency is to optimizethe cooling, in the sense of implementing cooling infrastructures controlschemes that avoid performing over-cooling of the servers.Towards this direction, this work investigates minimum cost linearquadratic control strategies for the problem of managing air cooled datacenters. We derive a physical and a black box model for a general datacenter, identify this model from real data, and then derive, present andtest in the eld a model based Linear-Quadratic Regulator (LQR) strategy that sets the optimal coolant temperature for each individual coolingunit. To validate the approach we compare the eld tests from the LQR strategy against classical Proportional-Integral-Derivative (PID) controlstrategies, and show through our experiments that it is possible to reducethe energy consumption with respect to the existing practices by severalpoints percent without harming the servers within the data center fromthermal perspectives.
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Maciel, Allan James Ferreira. "CONVERGÊNCIA DO ESTIMADOR RLS PARA ALGORITMOS DE PROGRAMAÇÃO DINÂMICA HEURÍSTICA." Universidade Federal do Maranhão, 2012. http://tedebc.ufma.br:8080/jspui/handle/tede/494.
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Previous issue date: 2012-09-28Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The union of methodologies for optimal control and dynamics programming has stimulated the development of algorithms for realization of discrete control systems of the type linear quadratic regulator (DLQR). The methodology is based on reinforcement learning methods based on temporal differences and approximate dynamic programming. The proposed method combines the approach of the value function by method RLS (recursive least squares) and approximate policy iteration schemes heuristic dynamic programming (HDP). The approach is directed to the assessment of convergence of the solution DLQR and the heuristic weighting matrices and of the utility function associated with DLQR. The investigation of convergence properties related to consistency, persistent excitation and polarization of the RLS estimator is performed. The methodology involved in a project achievements online DLQR controllers and is evaluated in a fourth order multivariable dynamic system.
A união das metodologias de controle ótimo e de programação dinâmica tem impulsionado o desenvolvimento de algoritmos para realizações de sistemas de controle discreto do tipo regulador linear quadrático (DLQR). A metodologia utilizada neste trabalho é fundamentada sobre métodos de aprendizagem por reforço baseados em diferenças temporais e programação dinâmica aproximada. O método proposto combina a aproximação da função valor através do método RLS (mínimos quadrados recursivos) e iteração de política aproximada em esquemas de programação dinâmica heurística (HDP). A abordagem é orientada para a avaliação da convergência da solução DLQR e para a sintonia heurística das matrizes de ponderação e da função de utilidade associada ao DLQR. É realizada a investigação das propriedades de convergência relacionadas à consistência, excitação persistente e polarização do estimador RLS. A metodologia contempla realizações de projetos de forma online de controladores DLQR e é avaliada em um sistema dinâmico multivariável de quarta ordem.
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SANTOS, Watson Robert Macedo. "Metodos para Solução da Equação HJB-Riccati via Famíla de Estimadores Parametricos RLS Simplificados e Dependentes de Modelo." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/1892.
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Due to the demand for high-performance equipments and the rising cost of energy, the industrial sector is developing equipments to attend minimization of the theirs operational costs. The implementation of these requirements generate a demand for projects and implementations of high-performance control systems. The optimal control theory is an alternative to solve this problem, because in its design considers the normative specifications of the system design, as well as those that are related to the operational costs. Motivated by these perspectives, it is presented the study of methods and the development of algorithms to the approximated solution of the Equation Hamilton-Jacobi-Bellman, in the form of discrete Riccati equation, model free and dependent of the dynamic system. The proposed solutions are developed in the context of adaptive dynamic programming that are based on the methods for online design of optimal control systems, Discrete Linear Quadratic Regulator type. The proposed approach is evaluated in multivariable models of the dynamic systems to evaluate the perspectives of the optimal control law for online implementations.
Devido a demanda por equipamentos de alto desempenho e o custo crescente da energia, o setor industrial desenvolve equipamentos que atendem a minimização dos seus custos operacionais. A implantação destas exigências geram uma demanda por projetos e implementações de sistemas de controle de alto desempenho. A teoria de controle ótimo é uma alternativa para solucionar este problema, porque considera no seu projeto as especificações normativas de projeto do sistema, como também as relativas aos seus custos operacionais. Motivado por estas perspectivas, apresenta-se o estudo de métodos e o desenvolvimento de algoritmos para solução aproximada da Equação Hamilton-Jacobi-Bellman, do tipo Equação Discreta de Riccati, livre e dependente de modelo do sistema dinâmico. As soluções propostas são desenvolvidas no contexto de programação dinâmica adaptativa (ADP) que baseiam-se nos métodos para o projeto on-line de Controladores Ótimos, do tipo Regulador Linear Quadrático Discreto. A abordagem proposta é avaliada em modelos de sistemas dinâmicos multivariáveis, tendo em vista a implementação on-line de leis de controle ótimo.
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Uzinski, Julio Cezar [UNESP]. "A state-space parameterization for perfect-reconstruction wavelet FIR filter banks with special orthonormal basis functions." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/146716.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. Para ilustrar o funcionamento e as vantagens da técnica proposta, alguns exemplos de decomposição de sinais no contexto de processamento de sinais mostrando que ela proporciona os mesmos coeficientes wavelet que a transformada wavelet rápida, e uma aplicação em controle através de realimentação dinâmica de estados também são apresentados nesta tese.
This thesis presents a state-space parameterization for the fast wavelet transform. This parameterization is based on orthonormal basis functions and finite impulse response filters at the same time, since the fast wavelet transform is an algorithm, which converts a signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite wavelet functions. Advantages presented by both proposals are incorporated. Finite impulse response systems have attractive properties, for instance, computational and analytical advantages, BIBO stability and robustness guarantee to some parameter changes, and others. On the other hand, orthonormal basis functions have some characteristics that make them attractive for dynamic systems modeling, examples are, output recursion absence, not requiring prior regression vector exact structure knowledge; possibility of increasing the model representation capacity by increasing the number of orthonormal functions employed; natural outputs uncoupling in multivariable models; tolerance to unmodeled dynamics, and others. Furthermore, the state-space realization is minimal. The contribution of this work consists in the development of a state-space realization for a wavelet filter bank, with the explicit presence of the parameters that can be freely adjusted, keeping perfect-reconstruction and orthonormality guarantees. In order to illustrate advantages and how the proposed technique works, some decomposition examples in signal processing context are presented showing that it provides the same wavelet coefficients as the fast wavelet transform, and an application on dynamic state feedback control is also presented in this thesis.
CNPq: 160545/2013-7
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Uzinski, Julio Cezar. "A state-space parameterization for perfect-reconstruction wavelet FIR filter banks with special orthonormal basis functions /." Ilha Solteira, 2016. http://hdl.handle.net/11449/146716.
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Orientador: Francisco Villarreal AlvaradoResumo: Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. ... (Resumo completo, clicar acesso eletrônico abaixo)
Doutor
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Ferreira, Ernesto Franklin Marçal. "Melhorias de estabilidade numérica e custo computacional de aproximadores de funções valor de estado baseados em estimadores RLS para projeto online de sistemas de controle HDP-DLQR." Universidade Federal do Maranhão, 2016. http://tedebc.ufma.br:8080/jspui/handle/tede/1687.
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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-06-23T20:34:27Z
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The development and the numerical stability analysis of a new adaptive critic algorithm to approximate the state-value function for online discrete linear quadratic regulator (DLQR) optimal control system design based on heuristic dynamic programming (HDP) are presented in this work. The proposed algorithm makes use of unitary transformations and QR decomposition methods to improve the online learning e-ciency in the critic network through the recursive least-squares (RLS) approach. The developed learning strategy provides computational performance improvements in terms of numerical stability and computational cost which aim at making possible the implementations in real time of optimal control design methodology based upon actor-critic reinforcement learning paradigms. The convergence behavior and numerical stability of the proposed online algorithm, called RLSµ-QR-HDP-DLQR, are evaluated by computational simulations in three Multiple-Input and Multiple-Output (MIMO) models, that represent the automatic pilot of an F-16 aircraft of third order, a fourth order RLC circuit with two input voltages and two controllable voltage levels, and a doubly-fed induction generator with six inputs and six outputs for wind energy conversion systems.
Neste trabalho, apresenta-se o desenvolvimento e a análise da estabilidade numérica de um novo algoritmo crítico adaptativo para aproximar a função valor de estado para o projeto do sistema de controle ótimo online, utilizando o regulador linear quadrático discreto (DLQR), com base em programação dinâmica heurística (HDP). O algoritmo proposto faz uso de transformações unitárias e métodos de decomposição QR para melhorar a e-ciência da aprendizagem online na rede crítica por meio da abordagem dos mínimos quadrados recursivos (RLS). A estratégia de aprendizagem desenvolvida fornece melhorias no desempenho computacional em termos de estabilidade numérica e custo computacional, que visam tornar possíveis as implementações em tempo real da metodologia do projeto de controle ótimo com base em paradigmas de aprendizado por reforço ator-crítico. O comportamento de convergência e estabilidade numérica do algoritmo online proposto, denominado RLSµ-QR-HDP-DLQR, são avaliados por meio de simulações computacionais em três modelos Múltiplas-Entradas e Múltiplas-Saídas (MIMO), que representam o piloto automático de uma aeronave F-16 de terceira ordem, um circuito de quarta ordem RLC com duas tensões de entrada e dois níveis de tensão controláveis, e um gerador de indução duplamente alimentados com seis entradas e seis saídas para sistemas de conversão de energia eólica.
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RÊGO, Patrícia Helena Moraes. "Aprendizagem por Reforço e Programação Dinâmica Aproximada para Controle Ótimo: Uma Abordagem para o Projeto Online do Regulador Linear Quadrático Discreto com Programação Dinâmica Heurística Dependente de Estado e Ação." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/1879.
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Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-30T15:33:12Z
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In this thesis a proposal of an uni ed approach of dynamic programming, reinforcement learning and function approximation theories aiming at the development of methods and algorithms for design of optimal control systems is presented. This approach is presented in the approximate dynamic programming context that allows approximating the optimal feedback solution as to reduce the computational complexity associated to the conventional dynamic programming methods for optimal control of multivariable systems. Speci cally, in the state and action dependent heuristic dynamic programming framework, this proposal is oriented for the development of online approximated solutions, numerically stable, of the Riccati-type Hamilton-Jacobi-Bellman equation associated to the discrete linear quadratic regulator problem which is based on a formulation that combines value function estimates by means of a RLS (Recursive Least-Squares) structure, temporal di erences and policy improvements. The development of the proposed methodologies, in this work, is focused mainly on the UDU T factorization that is inserted in this framework to improve the RLS estimation process of optimal decision policies of the discrete linear quadratic regulator, by circumventing convergence and numerical stability problems related to the covariance matrix ill-conditioning of the RLS approach.
Apresenta-se nesta tese uma proposta de uma abordagem uni cada de teorias de programação dinâmica, aprendizagem por reforço e aproximação de função que tem por objetivo o desenvolvimento de métodos e algoritmos para projeto online de sistemas de controle ótimo. Esta abordagem é apresentada no contexto de programação dinâmica aproximada que permite aproximar a solução de realimentação ótima de modo a reduzir a complexidade computacional associada com métodos convencionais de programação dinâmica para controle ótimo de sistemas multivariáveis. Especi camente, no quadro de programação dinâmica heurística e programação dinâmica heurística dependente de ação, esta proposta é orientada para o desenvolvimento de soluções aproximadas online, numericamente estáveis, da equação de Hamilton-Jacobi-Bellman do tipo Riccati associada ao problema do regulador linear quadrático discreto que tem por base uma formulação que combina estimativas da função valor por meio de uma estrutura RLS (do inglês Recursive Least-Squares), diferenças temporais e melhorias de política. O desenvolvimento das metodologias propostas, neste trabalho, tem seu foco principal voltado para a fatoração UDU T que é inserida neste quadro para melhorar o processo de estimação RLS de políticas de decisão ótimas do regulador linear quadrá- tico discreto, contornando-se problemas de convergência e estabilidade numérica relacionados com o mal condicionamento da matriz de covariância da abordagem RLS.
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Salazar, Cortés Jean Carlo. "Contribution to reliable control of dynamic systems." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/669250.
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This thesis presents sorne contributions to the field of Health-Aware Control (HAC) of dynamic systems.
In the first part of this thesis, a review of the concepts and methodologies related to reliability versus degradation and fault tolerant control versus health-aware control is presented. Firstly, in an attempt to unify concepts, an overview of HAC, degradation, and reliability modeling including some of the most relevant theoretical and applied contributions is given.
Moreover, reliability modeling is formalized and exemplified using the structure function, Bayesian networks (BNs) and Dynamic Bayesian networks (DBNs) as modeling tools in reliability analysis. In addition, some Reliability lmportance Measures (RIMs) are presented.
In particular, this thesis develops BNs models for overall system reliability analysis through the use of Bayesian inference techniques. Bayesian networks are powerful tools in system reliability assessment due to their flexibility in modeling the reliability structure of complex systems.
For the HAC scheme implementation, this thesis presents and discusses the integration of actuators health information by means of RIMs and degradation in Model Predictive Control (MPC) and Linear Quadratic Regulator algorithms.
In the proposed strategies, the cost function parameters are tuned using RIMs. The methodology is able to avoid the occurrence of catastrophic and incipient faults by monitoring the overall system reliability.
The proposed HAC strategies are applied to a Drinking Water Network (DWN) and a multirotor UAV system. Moreover, a third approach, which uses MPC and restricts the degradation of the system components is applied to a twin rotor system.
Finally, this thesis presents and discusses two reliability interpretations. These interpretations, namely instantaneous and expected, differ in the manner how reliability is evaluated and how its evolution along time is considered. This comparison is made within a HAC framework and studies the system reliability under both approaches.Aquesta tesi presenta algunes contribucions al camp del control basat en la salut dels components "Health-Aware Control" (HAC) de sistemes dinàmics. A la primera part d'aquesta tesi, es presenta una revisió dels conceptes i metodologies relacionats amb la fiabilitat versus degradació, el control tolerant a fallades versus el HAC. En primer lloc, i per unificar els conceptes, s'introdueixen els conceptes de degradació i fiabilitat, models de fiabilitat i de HAC incloent algunes de les contribucions teòriques i aplicades més rellevants. La tesi, a més, el modelatge de la fiabilitat es formalitza i exemplifica utilitzant la funció d'estructura del sistema, xarxes bayesianes (BN) i xarxes bayesianes dinamiques (DBN) com a eines de modelat i anàlisi de la fiabilitat com també presenta algunes mesures d'importància de la fiabilitat (RIMs). En particular, aquesta tesi desenvolupa models de BNs per a l'anàlisi de la fiabilitat del sistema a través de l'ús de tècniques d'inferència bayesiana. Les xarxes bayesianes són eines poderoses en l'avaluació de la fiabilitat del sistema gràcies a la seva flexibilitat en el modelat de la fiabilitat de sistemes complexos. Per a la implementació de l?esquema de HAC, aquesta tesi presenta i discuteix la integració de la informació sobre la salut i degradació dels actuadors mitjançant les RIMs en algoritmes de control predictiu basat en models (MPC) i control lineal quadràtic (LQR). En les estratègies proposades, els paràmetres de la funció de cost s'ajusten utilitzant els RIMs. Aquestes tècniques de control fiable permetran millorar la disponibilitat i la seguretat dels sistemes evitant l'aparició de fallades a través de la incorporació d'aquesta informació de la salut dels components en l'algoritme de control. Les estratègies de HAC proposades s'apliquen a una xarxa d'aigua potable (DWN) i a un sistema UAV multirrotor. A més, un tercer enfocament fent servir la degradació dels actuadors com a restricció dins l'algoritme de control MPC s'aplica a un sistema aeri a dos graus de llibertat (TRMS). Finalment, aquesta tesi també presenta i discuteix dues interpretacions de la fiabilitat. Aquestes interpretacions, nomenades instantània i esperada, difereixen en la forma en què s'avalua la fiabilitat i com es considera la seva evolució al llarg del temps. Aquesta comparació es realitza en el marc del control HAC i estudia la fiabilitat del sistema en tots dos enfocaments.
Esta tesis presenta algunas contribuciones en el campo del control basado en la salud de los componentes “Health-Aware Control” (HAC) de sistemas dinámicos. En la primera parte de esta tesis, se presenta una revisión de los conceptos y metodologíasrelacionados con la fiabilidad versus degradación, el control tolerante a fallos versus el HAC. En primer lugar, y para unificar los conceptos, se introducen los conceptos de degradación y fiabilidad, modelos de fiabilidad y de HAC incluyendo algunas de las contribuciones teóricas y aplicadas más relevantes. La tesis, demás formaliza y ejemplifica el modelado de fiabilidad utilizando la función de estructura del sistema, redes bayesianas (BN) y redes bayesianas diná-micas (DBN) como herramientas de modelado y análisis de fiabilidad como también presenta algunas medidas de importancia de la fiabilidad (RIMs). En particular, esta tesis desarrolla modelos de BNs para el análisis de la fiabilidad del sistema a través del uso de técnicas de inferencia bayesiana. Las redes bayesianas son herramientas poderosas en la evaluación de la fiabilidad del sistema gracias a su flexibilidad en el modelado de la fiabilidad de sistemas complejos. Para la implementación del esquema de HAC, esta tesis presenta y discute la integración de la información sobre la salud y degradación de los actuadores mediante las RIMs en algoritmos de control predictivo basado en modelos (MPC) y del control cuadrático lineal (LQR). En las estrategias propuestas, los parámetros de la función de coste se ajustan utilizando las RIMs. Estas técnicas de control fiable permitirán mejorar la disponibilidad y la seguridad de los sistemas evitando la aparición de fallos a través de la incorporación de la información de la salud de los componentes en el algoritmo de control. Las estrategias de HAC propuestas se aplican a una red de agua potable (DWN) y a un sistema UAV multirotor. Además, un tercer enfoque que usa la degradación de los actuadores como restricción en el algoritmo de control MPC se aplica a un sistema aéreo con dos grados de libertad (TRMS). Finalmente, esta tesis también presenta y discute dos interpretaciones de la fiabilidad. Estas interpretaciones, llamadas instantánea y esperada, difieren en la forma en que se evalúa la fiabilidad y cómo se considera su evolución a lo largo del tiempo. Esta comparación se realiza en el marco del control HAC y estudia la fiabilidad del sistema en ambos enfoques.
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Alepuz, Menéndez Salvador Simón. "Aportación al control del convertidor CC/CA de tres niveles." Doctoral thesis, Universitat Politècnica de Catalunya, 2004. http://hdl.handle.net/10803/6330.
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La presente tesis estudia, propone y realiza sus principales aportaciones en el campo del control para el convertidor CC/CA de tres niveles, sobre la topología denominada Neutral-Point-Clamped, aunque se puede extender a otras topologías y/o número de niveles. Se presenta una metodología de modelado que emplea funciones de conmutación de fase, el operador de promediado y la transformación D-Q, tal que los modelos obtenidos en el dominio D-Q contienen una información completa sobre la dinámica del sistema. La estrategia de conmutación se puede entender como una extensión de la estrategia PWM senoidal de dos a tres niveles. Esta estrategia es simple y no realiza el control de ninguna de las variables del sistema. En esta tesis, el controlador se encarga de regular todas las variables del sistema, incluido el equilibrio del bus de continua. Este es un enfoque diferente del convencional, donde el equilibrio del bus de continua se consigue mediante la elección adecuada de los estados redundantes del convertidor en la estrategia de conmutación, mientras que el resto de variables se regulan a través del controlador. Para la realización del controlador, se propone la técnica de control lineal multivariable LQR (Linear Quadratic Regulator), complementada con la técnica de control no lineal adaptativo denominada programación de ganancia (Gain Scheduling). Se presenta, además, una metodología de cálculo del controlador. Este control es versátil, abierto y adaptable. En cualquier caso, el controlador se puede adaptar a las necesidades concretas de cada aplicación. El cálculo del controlador se realiza mediante simulación con MatLab-Simulink. Los modelos matemáticos que emplean las funciones de conmutación del convertidor son aquellos que ofrecen un mejor compromiso entre velocidad de simulación y precisión. Para validar el control propuesto, se ha diseñado y construido un equipo experimental donde el controlador se ha mostrado aplicable, útil y eficaz en la regulación de las distintas cargas y aplicaciones experimentadas, incluso con carga no lineal, bajo diferentes condiciones de trabajo y variables a controlar, tanto en régimen permanente como en procesos transitorios. La rapidez y calidad de la respuesta transitoria es comparable a la de otros sistemas de control publicados. Es especialmente interesante el excelente control conseguido del equilibrio del bus de continua. Además, la robustez del control permite cancelar el error estacionario aunque diferentes parámetros del sistema presenten desviaciones significativas respecto los valores esperados. El uso de la programación de ganancia junto con la técnica LQR se ha mostrado muy efectivo, puesto que permite realizar diferentes tipos de control. Se ha comprobado la congruencia entre simulaciones y resultados experimentales obtenidos, lo que valida los modelos de simulación empleados y el proceso de diseño del controlador mediante simulación.This dissertation study, propose and carry out the main contributions in the field of three-level inverter control, using the topology Neutral-Point-Clamped, although results can be extended to other topologies and/or number of levels. A procedure for modelling is presented, based on line-switching functions, moving average operator and D-Q transformation. Then, the obtained models in D-Q frame contain complete information about system dynamics. Switching strategy is simple and can be considered as an extension of two-level sinusoidal PWM to three level. The system variables are not controlled by the switching strategy. In this work, all the system variables are controlled by the regulator, including DC-link balance. This control approach is different than the conventional one, where DC-link balance is achieved by means of a proper selection of redundant states in the switching strategy, and the other variables are controlled by the regulator. The regulator is based on the multivariable linear control technique LQR (Linear Quadratic Regulator), in combination with the non-linear adaptive control technique Gain Scheduling. Moreover, a methodology for the calculation of the controller is presented. This controller is versatile, open and adaptable. However, the controller can be built depending on the concrete specifications of each application. The controller is calculated by means of simulation using MatLab-Simulink. The mathematical models based on the switching functions of the converter give the best trade-off between simulation speed and precision. In order to validate the proposed controller, an experimental prototype has been designed and implemented. Experimental results show that the controller is useful and effective for the regulation of different loads and applications, even with non-linear loads, different operation points and variables to control, in steady-state and transitory operation. Dynamic response speed and quality are similar to other control systems in the literature. The DC-link balance control achieved is specially interesting. Furthermore, steady-state error is cancelled due to the robustness of the controller, even though significant deviation of different system parameters are present. The use of Gain-Scheduling in combination with LQR is effective, allowing the calculation of regulators with different control strategies. Good agreement between simulations and experimental results has been found. This result validates simulation models and the design method for the controller, based on simulations.
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Alepuz, Menéndez Salvador Simón. "Aportació al control del convertidor CC/CA de tres nivells." Doctoral thesis, Universitat Politècnica de Catalunya, 2004. http://hdl.handle.net/10803/6330.
Full textAbstract:
La presente tesis estudia, propone y realiza sus principales aportaciones en el campo del control para el convertidor CC/CA de tres niveles, sobre la topología denominada Neutral-Point-Clamped, aunque se puede extender a otras topologías y/o número de niveles. Se presenta una metodología de modelado que emplea funciones de conmutación de fase, el operador de promediado y la transformación D-Q, tal que los modelos obtenidos en el dominio D-Q contienen una información completa sobre la dinámica del sistema. La estrategia de conmutación se puede entender como una extensión de la estrategia PWM senoidal de dos a tres niveles. Esta estrategia es simple y no realiza el control de ninguna de las variables del sistema. En esta tesis, el controlador se encarga de regular todas las variables del sistema, incluido el equilibrio del bus de continua. Este es un enfoque diferente del convencional, donde el equilibrio del bus de continua se consigue mediante la elección adecuada de los estados redundantes del convertidor en la estrategia de conmutación, mientras que el resto de variables se regulan a través del controlador. Para la realización del controlador, se propone la técnica de control lineal multivariable LQR (Linear Quadratic Regulator), complementada con la técnica de control no lineal adaptativo denominada programación de ganancia (Gain Scheduling). Se presenta, además, una metodología de cálculo del controlador. Este control es versátil, abierto y adaptable. En cualquier caso, el controlador se puede adaptar a las necesidades concretas de cada aplicación. El cálculo del controlador se realiza mediante simulación con MatLab-Simulink. Los modelos matemáticos que emplean las funciones de conmutación del convertidor son aquellos que ofrecen un mejor compromiso entre velocidad de simulación y precisión. Para validar el control propuesto, se ha diseñado y construido un equipo experimental donde el controlador se ha mostrado aplicable, útil y eficaz en la regulación de las distintas cargas y aplicaciones experimentadas, incluso con carga no lineal, bajo diferentes condiciones de trabajo y variables a controlar, tanto en régimen permanente como en procesos transitorios. La rapidez y calidad de la respuesta transitoria es comparable a la de otros sistemas de control publicados. Es especialmente interesante el excelente control conseguido del equilibrio del bus de continua. Además, la robustez del control permite cancelar el error estacionario aunque diferentes parámetros del sistema presenten desviaciones significativas respecto los valores esperados. El uso de la programación de ganancia junto con la técnica LQR se ha mostrado muy efectivo, puesto que permite realizar diferentes tipos de control. Se ha comprobado la congruencia entre simulaciones y resultados experimentales obtenidos, lo que valida los modelos de simulación empleados y el proceso de diseño del controlador mediante simulación.This dissertation study, propose and carry out the main contributions in the field of three-level inverter control, using the topology Neutral-Point-Clamped, although results can be extended to other topologies and/or number of levels. A procedure for modelling is presented, based on line-switching functions, moving average operator and D-Q transformation. Then, the obtained models in D-Q frame contain complete information about system dynamics. Switching strategy is simple and can be considered as an extension of two-level sinusoidal PWM to three level. The system variables are not controlled by the switching strategy. In this work, all the system variables are controlled by the regulator, including DC-link balance. This control approach is different than the conventional one, where DC-link balance is achieved by means of a proper selection of redundant states in the switching strategy, and the other variables are controlled by the regulator. The regulator is based on the multivariable linear control technique LQR (Linear Quadratic Regulator), in combination with the non-linear adaptive control technique Gain Scheduling. Moreover, a methodology for the calculation of the controller is presented. This controller is versatile, open and adaptable. However, the controller can be built depending on the concrete specifications of each application. The controller is calculated by means of simulation using MatLab-Simulink. The mathematical models based on the switching functions of the converter give the best trade-off between simulation speed and precision. In order to validate the proposed controller, an experimental prototype has been designed and implemented. Experimental results show that the controller is useful and effective for the regulation of different loads and applications, even with non-linear loads, different operation points and variables to control, in steady-state and transitory operation. Dynamic response speed and quality are similar to other control systems in the literature. The DC-link balance control achieved is specially interesting. Furthermore, steady-state error is cancelled due to the robustness of the controller, even though significant deviation of different system parameters are present. The use of Gain-Scheduling in combination with LQR is effective, allowing the calculation of regulators with different control strategies. Good agreement between simulations and experimental results has been found. This result validates simulation models and the design method for the controller, based on simulations.
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Krejčí, Roman. "Řízení modelu v reálném čase." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221296.
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This diploma thesis deals with control the Ball on the wheel system in real time. In the first part there is made mathematical model of system, which is described by state equations. Then the laboratory model of Ball on the wheel system and its parts are described. The laboratory model consists servo drive, servo amplifier, microcontroller with real-time operating system and distance sensors. In the practical part of the thesis there is designed control of system by linear quadratic regulator and its implementation with control peripherals into microcontroller with real-time operating system. Ball on the wheel system is controlled by microcontroller, which sends a commands to servo amplifier by CAN bus.
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Cerqueira, Marcio Mendes. "Observadores de Estados para Sistemas de Medição Indireta e Controle RLQD-GA." Universidade Federal do Maranhão, 2010. http://tedebc.ufma.br:8080/jspui/handle/tede/432.
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Motivated by the necessity of efficient algorithms, it s presented the development of a methodology for the design and analysis of state observers in open and closed loops that are dedicated to monitoring and control of dynamic systems. The development of observers are based on OE models, description in state space and Kalman filter. The models are evaluated for temperature control of a aluminum cube that is inside of a sterilizer oven. In addition to the models assessment in terms of its ability to represent behavior of plants, these models also evaluated for the design of discrete linear quadric regulator DLQR that are tuned by genetic algorithms. The monitoring models are evaluated for open and closed loops structures that are represented by algorithms in terms of difference equations, these algorithms are seen as software core for the indirect measurement systems.
Motivado pela necessidade de algoritmos eficientes, apresenta-se o desenvolvimento de uma metodologia para projeto e análise de observadores de estado em malhas aberta e fechada que são dedicados a monitoração e controle de sistemas dinâmicos. O desenvolvimento dos observadores estão fundamentados em modelos OE, descrição no espaço de estados e filtro de Kalman. Os modelos são avaliados para o controle da temperatura de um cubo de alumínio que encontra-se no interior de uma estufa. Além das avaliações dos modelos em termos de sua habilidade em representar comportamento de plantas, estes são também avaliados para o projeto do regulador linear quadrático discreto (RQLD) que são sintonizados por algoritmos genéticos. Aplicação dos modelos para monitoração é avaliada nas estruturas das malhas aberta e fechada que são representadas por algoritmos em da equação à diferença, tendo em vistas o desenvolvimento de núcleos de software para os sistemas de medição indireta.
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Caldeira, Fabrício Reis. "Design of an automatic landing system using linear quadratic tracker." Instituto Tecnológico de Aeronáutica, 2008. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=725.
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This work presents the application of the Linear Quadratic Tracker (LQT) for the automatic landing system of passenger transport airplanes. The design method to achieve an autoland flare law with improved performance and disturbance rejection is described. With this method the design is direct and more formal thus avoiding the somewhat time consuming and more ad-hoc design iterations currently practice in industry. Although the design technique has been used for a autoland system, the approach is general enough to be used in other control applications. The structure of a traditional flare controller used for transport airplane and the LQT flare controller are presented. The performance of the flare control law designed based on LQT is compared against the performance of a traditional flare control law. Simulation time histories and Monte Carlo simulation results are presented. The time histories simulations cover the nominal and the most adverse conditions anticipated during the operation of the autoland system. The results show that the LQT law provides a more accurate path control and better disturbance rejection. The Monte Carlo simulation was made according to the certification requirements of an autoland system. The results show that the LQT controller provides reduced touchdown dispersion for the sink rate and distance at touchdown. The automatic landing system using LQT complies easily with the certification requirements, whereas the traditional system based on the classical design of autopilot inner loop/outer loop meets the certification requirements with smaller margins.
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Slabý, Vít. "Návrh a realizace demonstračního modelu dvojítého kyvadla." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-378727.
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This thesis describes the process of rebuilding an experimental model of a single pendulum on a cart into the double pendulum on a cart. The control algorithm in MATLAB/Simulink environment for stabilization of the pendulum in the inverse position is designed. For this purpose, LQR state feedback control was implemented. Also method for swinging the pendulum into inverse position from stable state (swing-up) was designed. Feedforward method was utilised for swing-up control. In the thesis, functionality of these algorithms is shown.
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Sá, Denis Fabrício Sousa de. "MODELOS BASEADOS EM REDES NEURAIS ARTIFICIAIS COM APLICAÇÃO EM CONTROLE INDIRETO DE TEMPERATURA." Universidade Federal do Maranhão, 2015. http://tedebc.ufma.br:8080/jspui/handle/tede/295.
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Previous issue date: 2015-04-10Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The representation of dynamic systems or plants via mathematical models occupies an important position in control system design that allow the performance evaluation of the controller during his development stage. These models are also used as an alternative to solve the problem of the hardness or impracticability to install sensors that measure the controlled variables, the dynamic systems representations enable non-invasive measurement of these variables. As consequence the designer has an alternative way to perform adaptive and optimal sensorless control for a given process. In this dissertation is presented a proposal for control systems schemas and algorithms, based on recurrent neural networks (ANN) and Box-Jenkins models, that are dedicated to sensorless or indirect control of dynamic systems. The proposed models and algorithms are associated with the systems identification and recurrent ANN approaches. The algorithms developed for the AAN training are Backpropagation Accelerated and RLS types that are compared with classical methods and strategies to obtain it online parameters of indirect control of system for a thermal plant, where the actuator is Peltier cell. The performance the parametric models of the plant and adaptive PID digital controllers and linear quadratic regulator (DLQR) that are the main elements of the sensorless temperature control system, are evaluated by means of hybrid simulations, where the algorithms implemented in micro controllers and the plant represented by mathematical models. The performance results of the proposed sensorless control algorithms are promissory, not only, in terms of the control system performance, but also due to the reexibility to deploy it in other dynamic systems.
A representação de sistemas dinâmicos ou plantas por meio modelos matemáticos ocupa uma posição relevante no projeto de sistemas de controle, permitindo que o projetista avalie o desempenho dos controladores durante a fase de desenvolvimento do projeto. Estes modelos também são utilizados para resolver o problema da dificuldade ou impossibilidade da inserção de sensores em plantas para medição de variáveis controladas, onde os modelos viabilizam a mediação não invasiva destas variáveis, fornecendo uma alternativa para realização do controle indireto adaptativo e ótimo de um dado processo. Nesta dissertação apresenta-se o desenvolvimento de modelos propostos baseados em redes neurais artificiais recorrentes para o controle sensorless ou indireto da planta. Os modelos propostos estão associados com as abordagens de Identificação de Sistemas e de RNA's recorrentes. OS algoritmos desenvolvidos para o treinamento das RNAs são do tipo Backpropagation acelerado e RLS, que são comparados com estratégias e métodos clássicos, para obtenção online dos parâmetros do sistema de controle indireto de uma planta térmica, tendo como atuador uma célula Peltier. Para uns de avaliação de desempenho do sistema de controle indireto da planta, os modelos paramétricos e controladores digitais adaptativos do tipo PID e regulador linear quadrático (DLQR) são avaliados por meio de simulações híbridas, sendo os algoritmos dos controladores implementados em microcontroladores e a planta representada por modelos matemáticos. Os resultados apresentados são promissores, não são sentido do desempenho do sistema de controle, mas também nos custos reduzidos para seu desenvolvimento, operação e flexibilidade de aplicação em outros sistemas dinâmicos.
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Yilmaz, Fatma Bilge. "A Mathematical Modeling And Approximation Of Gene Expression Patterns By Linear And Quadratic Regulatory Relations And Analysis Of Gene Networks." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605382/index.pdf.
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This thesis mainly concerns modeling, approximation and inference of gene regulatory
dynamics on the basis of gene expression patterns. The dynamical behavior
of gene expressions is represented by a system of ordinary dierential equations.
We introduce a gene-interaction matrix with some nonlinear entries, in particular,
quadratic polynomials of the expression levels to keep the system solvable. The
model parameters are determined by using optimization. Then, we provide the
time-discrete approximation of our time-continuous model. We analyze the approximating
model under the aspect of stability. Finally, from the considered models we
derive gene regulatory networks, discuss their qualitative features of the networks
and provide a basis for analyzing networks with nonlinear connections.
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Jackson, James Scott. "Enabling Autonomous Operation of Micro Aerial Vehicles Through GPS to GPS-Denied Transitions." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8709.
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Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-the-art in optimal control of quadrotors by utilizing the error-state formulation frequently utilized in state estimation. It is shown that performing optimal control directly over the error-state results in a vastly more computationally efficient system than competing methods while also dealing with the non-vector rotation components of the state in a principled way. In addition, real-time robust flight planning is considered with a method to navigate cluttered, potentially unknown scenarios with real-time obstacle avoidance. Robust state estimation is a critical component to reliable operation, and this dissertation focuses on improving the robustness of visual-inertial state estimation in a filtering framework by extending the state-of-the-art to include better modeling and sensor fusion. Further, this dissertation takes concepts from the visual-inertial estimation community and applies it to tightly-coupled GNSS, visual-inertial state estimation. This method is shown to demonstrate significantly more reliable state estimation than visual-inertial or GNSS-inertial state estimation alone in a hardware experiment through a GNSS-GNSS denied transition flying under a building and back out into open sky. Finally, this dissertation explores a novel method to combine measurements from multiple agents into a coherent map. Traditional approaches to this problem attempt to solve for the position of multiple agents at specific times in their trajectories. This dissertation instead attempts to solve this problem in a relative context, resulting in a much more robust approach that is able to handle much greater intial error than traditional approaches.
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Xiong, Hao. "Constrained expectation-maximization (EM), dynamic analysis, linear quadratic tracking, and nonlinear constrained expectation-maximation (EM) for the analysis of genetic regulatory networks and signal transduction networks." Thesis, [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2332.
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