Dissertations / Theses on the topic 'Nonlinear adaptive models'
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1
Harkness, John. "Walsh functions for the identification and control of nonlinear plants." Thesis, University of Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281832.
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Adam, Wettring. "Adaptive Filtering and Nonlinear Models for Post-processing of Weather Forecasts." Thesis, Linköpings universitet, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119642.
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Kalman filters have been used by SMHI to improve the quality of their forecasts. Until now they have used a linear underlying model to do this. In this thesis it is investigated whether the performance can be improved by the use of nonlinear models such as polynomials and neural networks. The results suggest that an improvement is hard to achieve by this approach and that it is likely not worth the effort to implement a nonlinear model.
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McCallum, Emma Clare. "Adaptive phase II clinical trial design using nonlinear dose-response models." Thesis, University of Cambridge, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709013.
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CERBONI, BAIARDI LORENZO. "Adaptive models of learning in complex physical and social systems." Doctoral thesis, Urbino, 2016. http://hdl.handle.net/11576/2630552.
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Mazumdar, Sanjay Kumar. "Adaptive control of nonlinear systems using neural networks /." Title page, contents and abstract only, 1995. http://web4.library.adelaide.edu.au/theses/09PH/09phm476.pdf.
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Ton, That Long. "Nonlinear control studies for circadian models in system biology." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/nonlinear-control-studies-for-circadian-models-in-system-biology(f616f360-99e4-4314-ba51-be7a49e9ff0e).html.
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Circadian rhythms exist in almost all of living species, and they occupy an important role in daily biological activities of these species. This thesis deals with reduction of measurements in circadian models, and recovery of circadian phases. Two mathematical models of circadian rhythms are considered, with a 3rd order model for Neurospora, and a 7th order model for Mammals. The reduction of measurements of circadian models is shown by the proposals of observer designs to the two mathematical models of circadian rhythms. Both mathematical models contain strong nonlinearities, which make the observer design challenging. Two observer designs, reduced-order and one-sided Lipschitz, are applied to the circadian models to tackle the nonlinearities. Reduced-order observer design is based on a state transformation to make certain nonlinearities have no impact on the observer errors, and the design of one-sided Lipschitz observer is based on systems with one-sided Lipschitz nonlinearities. Both observer designs are based on the existing methods in literature. The existing method of reduced-order observer has been applied to a class of multi-output nonlinear systems. A new reduced-order observer design which extends the existing one in literature is presented in this thesis. In this new reduced-order observer method, the observer error dynamics can be designed by choosing the observer gain, unlike the existing one, of which the observer error dynamics depend on the invariant zeros under certain input-output map. The recovery of circadian phases is carried out to provide a solution to phase shifts occurred in circadian disorders. The restoration of circadian phases is performed by the synchronizations of trajectories of a controlled model with trajectories of a reference model. The reference model and the controlled model have phase differences, and both these models are based on a given 3rd order model of Neurospora circadian rhythms. The phase differences are reflected by different initial conditions, and by parameter uncertainty. The synchronizations of the two models are performed by using back-stepping method for the case of different initial conditions, and by using adaptive back-stepping method for the remaining case. Several simulation studies of the proposed observer designs and the proposed schemes of synchronizations are carried out with the results shown in this thesis.
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Eckardt, Stefan Verfasser], and Carsten [Akademischer Betreuer] [Könke. "Adaptive heterogeneous multiscale models for the nonlinear simulation of concrete / Stefan Eckardt ; Betreuer: Carsten Könke." Weimar : Institut für Strukturmechanik, 2010. http://d-nb.info/1115806408/34.
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Strömberg, Eric. "Applied Adaptive Optimal Design and Novel Optimization Algorithms for Practical Use." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-308452.
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The costs of developing new pharmaceuticals have increased dramatically during the past decades. Contributing to these increased expenses are the increasingly extensive and more complex clinical trials required to generate sufficient evidence regarding the safety and efficacy of the drugs. It is therefore of great importance to improve the effectiveness of the clinical phases by increasing the information gained throughout the process so the correct decision may be made as early as possible. Optimal Design (OD) methodology using the Fisher Information Matrix (FIM) based on Nonlinear Mixed Effect Models (NLMEM) has been proven to serve as a useful tool for making more informed decisions throughout the clinical investigation. The calculation of the FIM for NLMEM does however lack an analytic solution and is commonly approximated by linearization of the NLMEM. Furthermore, two structural assumptions of the FIM is available; a full FIM and a block-diagonal FIM which assumes that the fixed effects are independent of the random effects in the NLMEM. Once the FIM has been derived, it can be transformed into a scalar optimality criterion for comparing designs. The optimality criterion may be considered local, if the criterion is based on singe point values of the parameters or global (robust), where the criterion is formed for a prior distribution of the parameters. Regardless of design criterion, FIM approximation or structural assumption, the design will be based on the prior information regarding the model and parameters, and is thus sensitive to misspecification in the design stage. Model based adaptive optimal design (MBAOD) has however been shown to be less sensitive to misspecification in the design stage. The aim of this thesis is to further the understanding and practicality when performing standard and MBAOD. This is to be achieved by: (i) investigating how two common FIM approximations and the structural assumptions may affect the optimized design, (ii) reducing runtimes complex design optimization by implementing a low level parallelization of the FIM calculation, (iii) further develop and demonstrate a framework for performing MBAOD, (vi) and investigate the potential advantages of using a global optimality criterion in the already robust MBAOD.
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Minggao, Wei. "Human Head Stiffness Rendering." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32743.
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The technology of haptics rendering has greatly enriched development in Multimedia applications, such as teleoperation, gaming, medical and etc., because it makes the virtual object touchable by the human operator(s) in real world. Human head stiffness rendering is significant in haptic interactive applications as it defines the degree of reality in physical interaction of a human avatar created in virtual environment. In a similar research, the haptic rendering approach has two main types: 1) Haptic Information Integration and 2) Deformation Simulation. However, the complexity in anatomic and geometric structure of a human head makes the rendering procedure challenging because of the issues of accuracy and efficiency. In this work, we propose a hybrid method to render the appropriate stiffness property onto a 3D head polygon mesh of an individual user by firstly studying human head's sophisticated deformation behaviour and then rendering such behaviour as the resultant stiffness property on the polygon mesh. The stiffness property is estimated from a semantically registered and shape-adapted skull template mesh as a reference and modeled from soft tissue's deformation behaviour in a nonlinear Finite Element Method (FEM) framework. To render the stiffness property, our method consists of different procedures, including 3D facial landmark detection, models semantic registration using Iterative Closest Point (ICP) technique, adaptive shape modification processed with a modified Weighted Free-Form Deformation (FFD) and FEM Simulation. After the stiffness property is rendered on a head polygon mesh, we perform a user study by inviting participants to experience the haptic feedback rendered from our results. According to the participants' feedback, the head polygon mesh's stiffness property is properly rendered as it satisfies their expectation.
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MANICKAM, NITHYA. "NONLINEAR AND ADAPTIVE CONTROL OF MODEL HELICOPTER." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1144639875.
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Nigro, Paulo Salvador Britto. "An adaptive model order reduction for nonlinear dynamical problems." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3144/tde-26122014-122046/.
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Model order reduction is necessary even in a time where the parallel processing is usual in almost any personal computer. The recent Model Reduction Methods are useful tools nowadays on reducing the problem processing. This work intends to describe a combination between POD (Proper Orthogonal Decomposition) and Ritz vectors that achieve an efficient Galerkin projection that changes during the processing, comparing the development of the error and the convergence rate between the full space and the projection space, in addition to check the stability of the projection space, leading to an adaptive model order reduction for nonlinear dynamical problems more efficient. This model reduction is supported by a secant formulation, which is updated by BFGS (Broyden - Fletcher - Goldfarb - Shanno) method to accelerate convergence of the model, and a tangent formulation to correct the projection space. Furthermore, this research shows that this method permits a correction of the reduced model at low cost, especially when the classical POD is no more efficient to represent accurately the solution.A Redução de ordem de modelo é necessária, mesmo em uma época onde o processamento paralelo é usado em praticamente qualquer computador pessoal. Os recentes métodos de redução de modelo são ferramentas úteis nos dias de hoje para a redução de processamento de um problema. Este trabalho pretende descrever uma combinação entre POD (Proper Orthogonal Decomposition) e vetores de Ritz para uma projecção de Galerkin eficiente que sofre alterações durante o processamento, comparando o desenvolvimento do erro e a taxa de convergência entre o espaço total e o espaço de projeção, além da verificação de estabilidade do espaço de projeção, levando a uma redução de ordem do modelo adaptativo mais eficiente para problemas dinâmicos não-lineares. Esta redução de modelo é assistida por uma formulação secante, que é atualizado pela formula de BFGS (Broyden - Fletcher- Goldfarb - Shanno) com o intuito de acelerar a convergência do modelo, e uma formulação tangente para a correção do espaço de projeção. Além disso, esta pesquisa mostra que este método permite a correção do modelo reduzido com baixo custo, especialmente quando o clássico POD não é mais eficiente para representar com precisão a solução.
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Lopez, Brett Thomas. "Adaptive robust model predictive control for nonlinear systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122395.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 115-124).
Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube centered around a desired nominal trajectory (generated online). While tube MPC regains tractability, there are several theoretical and practical problems that must be solved for it to be used in real-world scenarios. First, the decoupled trajectory and control design is inherently suboptimal, especially for systems with changing objectives or operating conditions. Second, no existing tube MPC framework is able to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. And third, the inability to reduce state-dependent uncertainty through online parameter adaptation/estimation leads to systematic error in the trajectory design. This thesis aims to address these limitations by developing a computationally tractable nonlinear tube MPC framework that is applicable to a broad class of nonlinear systems.
"This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374, by the DARPA Fast Lightweight Autonomy (FLA) program, by the NASA Convergent Aeronautics Solutions project Design Environment for Novel Vertical Lift Vehicles (DELIVER), and by ARL DCIST under Cooperative Agreement Number W911NF- 17-2-0181"--Page 7.
by Brett T. Lopez.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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CASSARO, MARIO. "Model Reference Adaptive Control Laws: Application to Nonlinear Aeroelastic Systems." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2605774.
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Nonlinear Aeroelastic Control has been a research topic of great interest for
the past few decades. Dierent approaches has been attempted aiming to obtain
better accuracy in the model dynamics description and better control
performance. As far as the aeroelastic mathematical model is concerned,
the scientic world converged in the use of a bi-dimension, two degree of
freedom, plunging and pitching, wing section model, of which the bigger
advantages are to be reproducible experimentally with an appropriate wind
tunnel apparatus and to allow LCO (Limit Cycle Oscillation) exhibition
at low values of wind speed, facilitating parametric studies of the nonlinear
aeroelastic system and its control architecture. A parametric analysis
of the linearized system, typical of aircraft
ight dynamic studies, is employed
to verify and validate the model dynamic properties dependency,
focusing in particular to the eect of stiness reduction as means of failure
simulation. In fact, despite of the recent years
ourishing literature
on aeroelastic adaptive controls, there is a noted lack of robustness and
sensitivity analysis with respect to structural proprieties degradation which
might be associated with a structural failure. Structural mode frequencies
and aeroelastic response, including Limit Cycle Oscillations (LCOs) characteristics,
are signicantly aected by changes in stiness. This leads to
a great interest in evaluating and comparing the adaptation capabilities
of dierent control architectures subjected to large plant uncertainties and
unmodeled dynamics. Motivated by the constantly increasing diusion of
the new L
adaptive control theory, developed for the control of uncertain
non-autonomous nonlinear systems, and by the fact that its application to
aeroelasticity is in its infancy, a deep investigation of this control scheme
properties and performance drew our attention. The new control theory
is conceptually similar to the Model Reference Adaptive Control (MRAC)
theory to which has often been compared indeed for performance evaluation
purpose. In this dissertation, a comprehensive analysis of the new control
theory is obtained by performance evaluation and comparison of four dierent
control schemes, two MRAC and two L
1
, focusing the attention on the
states and control input time response, adaptive law parameters' convergence,
transient evolution and fastness, and robustness in terms of tolerance
of uncertainties in o-design conditions. The objective is pursued by re-
writing the aeroelastic model nonlinear equations of motion in an amenable
form to the development of the four dierent control laws. The control laws
are then derived for the appropriate class of plant which the system belongs
to, and design parameter obtained, when necessary, following the mathematical
formulation of the control theories developers. A simulation model
is employed to carry out the numerical analysis and to outline pros and cons
of each architecture, to obtain as nal result the architecture that better ts
the nonlinear aeroelastic problem proposed. This methodology is used to
guarantee a certain robustness in controlling a novel actuation architecture,
developed for
utter suppression of slender/highly
exible wing, based on
a coordinated multiple spoiler stripe, located at fteen percent of the mean
aerodynamic chord. The control actuation system design, manufacturing
and experimental wind tunnel test is part of the dissertation. Two dierent
experimental setup are developed for two dierent purpose. First, a six-axis
force balance test is carried out to validate the numerical aerodynamic results
obtained during the validation process, and to collect the aerodynamic
coecient date base useful for the development of the simulation model of
the novel architecture. The second experimental apparatus, is a two degree
of freedom, plunging/pitching, system on which the prototyped wing section
is mounted to obtain LCO aeroelastic response during wind tunnel experiment.
The nonlinear aeroelastic mathematical formulation is modied to
take into account of the novel actuation architecture and, coupled with the
more robust MRAC control laws derived for the previous model, serves as
benchmark for properties assessment of the overall architecture, for
utter
suppression. The novel control actuation architecture proposed, is successfully
tested in wind tunnel experimentation conrming the validity of the
proposed solution. This dissertation provides a step forward to the denition
of certain MRAC control schemes properties, and together provides a
novel actuation solution for
utter suppression which demonstrates to be a
viable alternative to classical leading and/or trailing-edge
ap architecture or to be used as redundancy to them.
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Davenport, James Michael. "An Adaptive Dose Finding Design (DOSEFIND) Using A Nonlinear Dose Response Model." VCU Scholars Compass, 2007. http://hdl.handle.net/10156/13.
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Bohn, Christian. "Recursive parameter estimation for nonlinear continuous time systems through sensitivity model based adaptive filters." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=959575170.
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Gaunersdorfer, Andrea, and Cars H. Hommes. "Nonlinear adaptive beliefs and the dynamics of financial markets. The role of the evolutionary fitness measure." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2001. http://epub.wu.ac.at/434/1/document.pdf.
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We introduce a simple asset pricing model with two types of adaptively learning traders, fundamentalists and technical traders. Traders update their beliefs according to past performance and to market conditions. The model generates endogenous price fluctuations and captures some stylized facts observed in real returns data, such as excess volatility, fat tails of returns distributions, volatility clustering, and long memory. We show that the results are quite robust w.r.t. to different choices for the performance measure. (author's abstract)Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
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Yang, Shu. "Modeling and Control of Tensegrity-Membrane Systems." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71686.
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Tensegrity-membrane systems are a class of new bar-tendon-membrane systems. Such novel systems can be treated as extensions of tensegrity structures and are generally lightweight and deployable. These two major advantages enable tensegrity-membrane systems to become one of the most promising candidates for lightweight space structures and gossamer spacecraft.
In this dissertation, modeling and control of tensegrity-membrane systems is studied. A systematic method is developed to determine the equilibrium conditions of general tensegrity-membrane systems. Equilibrium conditions can be simplified when the systems are in symmetric configurations. For one-stage symmetric systems, analytical equilibrium conditions can be determined.
Three mathematical models are developed to study the dynamics of tensegrity-membrane systems. Two mathematical models are developed based on the nonlinear finite element method. The other model is a control-oriented model, which is suitable for control design. Numerical analysis is conducted using these three models to study the mechanical properties of tensegrity-membrane systems.
Two control strategies are developed to regulate the deployment process of tensegrity-membrane systems. The first control strategy is to deploy the system by a nonlinear adaptive controller and use a linear H∞ controller for rapid system stabilization. The second control strategy is to regulate the dynamics of tensegrity-membrane systems using a linear parameter-varying (LPV) controller during system deployment. A gridding method is employed to discretize the system operational region in order to carry out the LPV control synthesis.Ph. D.
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Castillo, Carlos L. "Fault-tolerant adaptive model predictive control using joint kalman filter for small-scale helicopter." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002711.
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Gunbatar, Yakup. "Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406160002.
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Zhang, Li Feng. "Novel correlation test based model validation methodologies for nonlinear system identification, intelligent modelling and adaptive noise cancellation." Thesis, University of the West of England, Bristol, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444493.
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Zhang, Cheng. "A contribution to the nonlinear control of floating wind turbines." Thesis, Ecole centrale de Nantes, 2021. http://www.theses.fr/2021ECDN0009.
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Les éoliennes flottantes permettent d’utiliser l’abondante ressource en vent présente au large des côtes, et sont considérées comme une source prometteuse d’énergie renouvelable. Cependant, en raison de dynamiques supplémentaires introduites par la plateforme flottante (notamment, le tangage), le contrôle d’une éolienne flottante doit être pensée afin de stabiliser le système tout en optimisant la production d’énergie. Ce travail est consacré à la commande non linéaire d’éoliennes flottantes dans la région III, la classe de lois de commande proposée nécessitant une connaissance réduite en terme de modélisation du système. Les objectifs de la commande sont de maintenir la puissance produite à sa valeur nominale, tout en li mitant le mouvement de tangage de la plateforme et les charges de fatigue sur la structure. Tout d’abord, une loi de commande adaptative basée sur le supertwisting est proposée, avec notamment une loi d’adaptation du gain très simple. Ensuite, en utilisant un contrôle collectif du pas des pales, ce nouvel algorithme de commande est appliqué sur un modèle d’éolienne flottante non linéaire et comparé à d’autres commandes adaptatives par modes glissants d’ordre 2. Dans un second temps, une machine synchrone à aimants permanents est supposée être installée dans l’éolienne flottante. L’utilisation du pas des pales (approche collective) et du couple du générateur permet d’atteindre les objectifs, à partir de lois de commande basées sur une approche adaptative par mode de glissement d’ordre 2. Une troisième partie est consacrée à l’étude d’une commande individuelle du pas des pales combinée à une commande collective. Il est montré qu’un tel algorithme limite la charge de fatigue des pales. Enfin, des lois de commande sont appliquées et comparées sur un système expérimental d’éolienne flottante placé dans un bassin à houle. Les performances des lois de commande basées sur les modes glissants sont évaluées par rapport à des approches de commande linéaire telles qu’un PI à gain variable, et une commande linéaire quadratiqueFloating wind turbines allow the use of the abundant wind resource in ocean area and are considered as a promising solution of renewable energy. However, due to the additional dynamics (especially the platform pitch motion) introduced by the floating platform, the control of a floating wind turbine must take such pitch motion into consideration to stabilize the system meanwhile optimizing the power output. This work is dedicated to the nonlinear control of floating wind turbines in region III, this class of controllers requiring reduced knowledge of system modeling and parameter. The control objectives are to maintain the power output at its rated value, to reduce the platform pitch motion and to limit the fatigue load. Firstly, a simplified adaptive super-twisting is proposed. Then, by using collective blade pitch control, this algorithm and other adaptive high order sliding model algorithms are applied on a nonlinear floating wind turbine model. Secondly, a permanent magnet synchronous generator is supposed to be installed in the floating wind turbine. Both collective blade pitch control and generator torque control based on adaptive high-order sliding mode control are used to achieve the control objectives. Thirdly, individual blade pitch control combined with collective blade pitch control is employed. Such algorithm further reduces the fatigue load of blades. Finally, the proposed simplified adaptive super-twisting algorithm is validated on an experimental floating wind turbine set-up (with a spar-buoy platform) in a wave tank, and the control performances are evaluated versus linear control approaches such as gain-scheduled PI and linear–quadratic regulators
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KARIMSHOUSHTARI, MILAD. "Design of Experiments for Nonlinear System Identification." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2751496.
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Zhang, Huaiye. "Bayesian Approach Dealing with Mixture Model Problems." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/37681.
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In this dissertation, we focus on two research topics related to mixture models. The first topic is Adaptive Rejection Metropolis Simulated Annealing for Detecting Global Maximum Regions, and the second topic is Bayesian Model Selection for Nonlinear Mixed Effects Model.
In the first topic, we consider a finite mixture model, which is used to fit the data from heterogeneous populations for many applications. An Expectation Maximization (EM) algorithm and Markov Chain Monte Carlo (MCMC) are two popular methods to estimate parameters in a finite mixture model. However, both of the methods may converge to local maximum regions rather than the global maximum when multiple local maxima exist. In this dissertation, we propose a new approach, Adaptive Rejection Metropolis Simulated Annealing (ARMS annealing), to improve the EM algorithm and MCMC methods. Combining simulated annealing (SA) and adaptive rejection metropolis sampling (ARMS), ARMS annealing generate a set of proper starting points which help to reach all possible modes. ARMS uses a piecewise linear envelope function for a proposal distribution. Under the SA framework, we start with a set of proposal distributions, which are constructed by ARMS, and this method finds a set of proper starting points, which help to detect separate modes. We refer to this approach as ARMS annealing. By combining together ARMS annealing with the EM algorithm and with the Bayesian approach, respectively, we have proposed two approaches: an EM ARMS annealing algorithm and a Bayesian ARMS annealing approach. EM ARMS annealing implement the EM algorithm by using a set of starting points proposed by ARMS annealing. ARMS annealing also helps MCMC approaches determine starting points. Both approaches capture the global maximum region and estimate the parameters accurately. An illustrative example uses a survey data on the number of charitable donations.
The second topic is related to the nonlinear mixed effects model (NLME). Typically a parametric NLME model requires strong assumptions which make the model less flexible and often are not satisfied in real applications. To allow the NLME model to have more flexible assumptions, we present three semiparametric Bayesian NLME models, constructed with Dirichlet process (DP) priors. Dirichlet process models often refer to an infinite mixture model. We propose a unified approach, the penalized posterior Bayes factor, for the purpose of model comparison. Using simulation studies, we compare the performance of two of the three semiparametric hierarchical Bayesian approaches with that of the parametric Bayesian approach. Simulation results suggest that our penalized posterior Bayes factor is a robust method for comparing hierarchical parametric and semiparametric models. An application to gastric emptying studies is used to demonstrate the advantage of our estimation and evaluation approaches.Ph. D.
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Jaramillo, López Fernando. "Control and Model Identification on Renewable Energy Systems." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112240.
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La situation compromettante de l'environnement due à la pollution, et les coûts élevés des combustibles fossiles ont engagé des nouvelles politiques et réglementations et ont fortement incité l’augmentation de l’utilisation de nouvelles sources d'énergie renouvelables. De nombreux pays dans le monde ont augmenté de façon importante le développement de ces sources d'énergie. Deux des systèmes d'énergies renouvelables les plus couramment utilisés sont les systèmes éoliens (SE) et les systèmes photovoltaïques (SP). SE convertissent l'énergie du vent en énergie électrique au moyen d'un processus électromécanique et SP convertissent directement l'énergie solaire en énergie électrique au moyen d'un processus semi-conducteur. Ces systèmes présentent de nombreux défis qui doivent être résolus afin de gagner du terrain sur les systèmes d'énergies traditionnelles. L'un de ces défis est d'augmenter l'efficacité du système avec la commande des éléments de puissance. Afin d'atteindre cet objectif, il est nécessaire de mieux comprendre le comportement dynamique de ces systèmes et de développer des nouveaux modèles mathématiques et des nouvelles techniques de commande. Ces techniques nécessitent souvent des informations du système qui ne sont pas disponibles --- ou sont trop chères si on devait les mesurer. Pour résoudre ce problème, il est nécessaire de créer des algorithmes qui puissent estimer cette information, cependant, ce n'est pas une tâche facile, car les signaux des sources d'énergie dans SE et SP (c.-à-d. la vitesse du vent, rayonnement solaire, température) entrent dans les modèles mathématiques par une relation non linéaire. Ces algorithmes doivent pouvoir estimer ces signaux --- ou les signaux qui dépendent d’eux--- avec une bonne précision. Aussi, il est nécessaire de concevoir des lois de commande qui opèrent les systèmes à leur point maximum de puissance. Dans ce travail, nous proposons des nouveaux algorithmes d'estimation et des lois de commande qui sont liés à l'augmentation de l'efficacité énergétique dans SE et SP. Des travaux antérieurs liés à l'estimation des signaux mentionnés, les considéraient comme constants. Dans cette thèse, les algorithmes d'estimation proposés considèrent l'état variable des ces signaux. Dans toutes ces nouvelles propositions, la stabilité asymptotique est prouvée en utilisant les théories de Lyapunov. Les lois de commande sont calculées en utilisant les modèles non linéaires des systèmes. En outre, certaines des ces solutions sont étendues au cas général, qui peut être utilisé sur une large classe des systèmes non linéaires. Le premier, est un estimateur de paramètres pour les systèmes non linéaires. Il permet d'estimer les paramètres non linéaires variant dans le temps. La deuxième proposition est la conception d’un schéma pour une classe de systèmes non linéaires adaptatifs qui permet de compenser les incertitudes et les perturbations qui satisfont à la "condition de correspondance"The compromising situation of the environment due to pollution, and the high costs of the fossil fuels have originated new policies and regulations that have stimulating the interest on alternative energy sources. Many countries around the world have increased in an important way the penetration of these energy sources. Two of the most widely used renewable energy systems are the wind turbines systems (WTS) and the photovoltaic systems (PVS). WTS convert wind energy in electric energy by means of an electromechanical process and PVS convert solar energy directly in electric energy by means of a semiconductive process. These systems show many challenges that need to be solved in order to gain ground to the traditional energy systems. One of these challenges is increase the overall system efficiency by controlling the power conditioning elements. In order to achieve this, is necessary to better understand the dynamic behavior of these systems and develop new mathematical models and new control techniques. These techniques often require system information that is not possible ---or is too expensive--- measure. In order to solve this problem, is necessary to create algorithms that are able to estimate this information, however, this is not an easy task, because the signals of the energy sources in WTS and PVS (i.e., wind speed, irradiance, temperature) enter in the mathematical models in a nonlinear relation. These algorithms have to be able to estimate these signals ---or the signals that depend on them--- with good precision. Also, it is necessary to design control laws that operate the systems at their maximum power point. In this work, we propose novel estimation algorithms and control laws that are related with the increase of the energetic efficiency in WTS and PVS. Previous works related with estimation of the mentioned signals considered them as constants. In this thesis, the proposed estimation algorithms consider the time-varying condition of these signals. In all of these novel propositions, uniform asymptotic stability is proved using Lyapunov theories. The control laws are derived using the overall nonlinear models of the systems. In addition, some of these solutions are extended to the general case, which can be used on a large-class of nonlinear systems. The first one, is a novel parameter estimator for nonlinear systems. It allows to estimate time-varying nonlinear parameters. The second general proposition is a framework for a class of adaptive nonlinear systems that allows to compensate for uncertainties and perturbations that satisfy the matching condition
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Wirsching, Leonard [Verfasser], and Hans Georg [Akademischer Betreuer] Bock. "Multi-Level Iteration Schemes with Adaptive Level Choice for Nonlinear Model Predictive Control / Leonard Wirsching ; Betreuer: Hans Georg Bock." Heidelberg : Universitätsbibliothek Heidelberg, 2018. http://d-nb.info/1177251639/34.
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Davidson, Paul R. "Computational modelling of the human motor control system: Nonlinear enhancement of the adaptive model theory through simulation and experiment." Thesis, University of Canterbury. Electrical & Computer Engineering, 2001. http://hdl.handle.net/10092/4567.
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Adaptive Model Theory (AMT) proposes that the brain forms and adaptively maintains inverse models of the world around it for adaptive feedforward control. This leading motor control theory unites principles of neurobiology, psychology and engineering. A modified version of AMT was developed with the capacity to control nonlinear systems, to predict signals with nonlinear statistical characteristics, and to perform simultaneous feedback and feedforward adaptive control. The modified version is called nonlinear Adaptive Model Theory or nAMT. An experimental study was also performed investigating inverse model formation in the human motor control system, the results of which were then compared with the nAMT model.
A nonlinear dynamic system identification method was developed for nAMT to replace the linear structures employed by AMT. This method employs a neurobiologically-inspired locally-recurrent neural-network structure. A multi-layer adaptation algorithm was also developed specifically for this structure. Nonlinear AutoRegressive Moving-Average (NARMA) adaptive predictor structures replace the linear Moving Average (MA) predictor circuits used in AMT. Adaptive feedback control is augmented using a nonlinear dynamic forward model observer to improve the quality of the estimated response signal. Nonlinear dynamic inverse models are formed by placing the forward model in an internal feedback loop in which the gain function is adjusted to maintain stability.
The internal inverse model motor-control hypothesis was tested experimentally in a study looking at human open-loop performance in a tracking task. The study was aimed at directly demonstrating the formation of an internal inverse model of a novel visuomotor relationship for feedforward control in the brain. The study involved 20 normal adult subjects who performed a pursuit random tracking task with a steering wheel for input. During learning the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Results showed a transfer of learning from the unblanked runs to the blanked runs for a static nonlinear system (14% median improvement between first 4 and last 4 runs, p = .001) thereby demonstrating adaptive feedforward control in the nervous system. No such transfer was observed for a dynamic linear system, indicating a dominant adaptive feedback control component. The observed open-loop responses showed a high-pass frequency response which could not be explained using traditional control-systems motor control models.
Experimental results were compared with simulated results from the nAMT model. Results from the experimental study were used to verify and tune the computational model. The resulting simulations produced effects that mirrored the closed- and openloop characteristics of the experimental response trajectories. This supports the claim that an internal feedback loop is used for the inversion of external systems in the human brain. Other control-systems models (both AMT and feedback-error learning) would require substantial ad hoc modification to reproduce the observed disparity between closed- and open-loop results. In contrast, nAMT naturally reproduced the effect as a consequence of its novel nonlinear inversion method. In nAMT an inverse model is formed by embedding a forward model in an internal feedback loop incorporating a low derivative gain. The derivative loop-gain caused the inverse model to be relatively inaccurate at low frequencies, for which the feedback control loop was adequate, but to be increasingly accurate at higher frequencies. Maintenance of the loop-gain at the lowest possible levels maximizes the internal stability of the inverse. The simulation work confirmed that the nAMT model is capable of reproducing human behaviour under a wide range of conditions.
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Nguyen, Chuong Hoang. "Adaptive Predictor-Based Output Feedback Control of Unknown Multi-Input Multi-Output Systems: Theory and Application to Biomedical Inspired Problems." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71312.
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Functional Electrical Stimulation (FES) is a technique that applies electrical currents to nervous tissue in order to actively induce muscle contraction. Recent research has shown that FES provides a promising treatment to restore functional tasks due to paralysis caused by spinal cord injury, head injury, and stroke, to mention a few. Therefore, the overarching goal of this research work is to develop FES controllers to enable patients with movement-disorder to control their limbs in a desired manner and, in particular, to aid Parkinson's patients to suppress hand tremor. In our effort to develop strategies for muscle stimulation control, we first implement a model-based control technique assuming that all the states are measurable. The Hill-type muscle model coupled with a simplified 2DoF model of the arm is used to study the performance of our proposed adaptive sliding mode controller for simulation purpose. However, in the more practical situations, human limb dynamics are extremely complicate and it is inadequate to use model based controllers, especially considering there are still technical limitations that allow in vivo measurements of muscle activity. To tackle these challenges, we have developed output feedback adaptive control approaches for a class of unknown multi-input multi-output systems. Such control strategies are first developed for linear systems, and then extended to the nonlinear case. The proposed controllers, supported by experimental results, require minimum knowledge of the system dynamics and avoid many restrictive assumptions typically found in the literature. Therefore, we expect that the results introduced in this dissertation can provide a solution for a wide class of nonlinear uncertain systems, with focus on practical issues such as partial state measurement and the presence of mismatched uncertainties.Ph. D.
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Mannava, Anusha. "Adaptive Control of Nonminimum Phase Aerospace Vehicles- A Case Study on Air-Breathing Hypersonic Vehicle Model." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1503265018577074.
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Yan, Xinming. "Development of robust control based on sliding mode for nonlinear uncertain systems." Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0012.
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Le travail de thèse présenté dans ce mémoire s’inscrit dans le cadre du développement de lois de commande pour des systèmes non linéaires incertains, basées sur la théorie des modes glissants. Les méthodes classiques de la commande par modes glissants sont des lois de commande par retour d’état, où la variable de glissement et ses dérivées sont nécessaires. Le premier objectif de cette thèse est de proposer des lois de commande par modes glissants d’ordre supérieur avec une réduction de l’ordre de dérivation de la variable de glissement. Le deuxième objectif est de combiner les nouvelles lois de commande avec un mécanisme de gain adaptatif. L’utilisation d’un gain adaptatif permet de simplifier le réglage du gain, de réduire le temps de convergence et d’améliorer la précision. Enfin, l’applicabilité de ces approches est démontrée à travers leur application au banc d’essais électropneumatique de l’IRCCyN, et à un système volant à trois degrés de libertéThis work deals with the development of control laws for nonlinear uncertain systems based onsliding mode theory. The standard sliding mode control approaches are state feedback ones, in which the sliding variable and its time derivatives are required. This first objective of this thesis is to propose high order sliding mode control laws with a reduced use of sliding variable time derivatives. The contributions are made for the second and third order sliding mode control. The second objective is to combine the proposed control laws with a gain adaptation mechanism. The use of adaptive gain law allows to simplify the tuning process, to reduce the convergence time and to improve the accuracy. Finally, the applicability of the proposed approaches is shown on IRCCyN pneumatic benchmark. Applications are also made on 3DOF flying system
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GarcÃa, Z. Yohn E. "Fuzzy logic in process control: A new fuzzy logic controller and an improved fuzzy-internal model controller." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/2529.
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Two fuzzy controllers are presented. A fuzzy controller with intermediate variable designed for cascade control purposes is presented as the FCIV controller. An intermediate variable and a new set of fuzzy logic rules are added to a conventional Fuzzy Logic Controller (FLC) to build the Fuzzy Controller with Intermediate Variable (FCIV). The new controller was tested in the control of a nonlinear chemical process, and its performance was compared to several other controllers. The FCIV shows the best control performance regarding stability and robustness. The new controller also has an acceptable performance when noise is added to the sensor signal. An optimization program has been used to determine the optimum tuning parameters for all controllers to control a chemical process. This program allows obtaining the tuning parameters for a minimum IAE (Integral absolute of the error). The second controller presented uses fuzzy logic to improve the performance of the convention
al internal model controller (IMC). This controller is called FAIMCr (Fuzzy Adaptive Internal Model Controller). Twofuzzy modules plus a filter tuning equation are added to the conventional IMC to achieve the objective. The first fuzzy module, the IMCFAM, determines the process parameters changes. The second fuzzy module, the IMCFF, provides stability to the control system, and a tuning equation is developed for the filter time constant based on the process parameters. The results show the FAIMCr providing a robust response and overcoming stability problems. Adding noise to the sensor signal does not affect the performance of the FAIMC.The contributions presented in this work include:The development of a fuzzy controller with intermediate variable for cascade control purposes. An adaptive model controller which uses fuzzy logic to predict the process parameters changes for the IMC controller. An IMC filter tuning equation to update the filter time constant based in the process paramete
rs values. A variable fuzzy filter for the internal model controller (IMC) useful to provide stability to the control system.
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Li, Hancao. "Modeling and control of a pressure-limited respirator and lung mechanics." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47667.
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The lungs are particularly vulnerable to acute, critical illness. Respiratory failure can result not only from primary lung pathology, such as pneumonia, but also as a secondary consequence of heart failure or inflammatory illness, such as sepsis or trauma. When this occurs, it is essential to support patients with mechanical ventilation while the fundamental disease process is addressed. The goal of mechanical ventilation is to ensure adequate ventilation, which involves a magnitude of gas exchange that leads to the desired blood level of carbon dioxide, and adequate oxygenation that ensures organ function. Achieving these goals is complicated by the fact that mechanical ventilation can actually cause acute lung injury, either by inflating the lungs to excessive volumes or by using excessive pressures to inflate the lungs. Thus, the challenge to mechanical ventilation is to produce the desired blood levels of carbon dioxide and oxygen without causing further acute lung injury.
In this research, we develop an analysis and control synthesis framework for a pressure-limited respirator and lung mechanics system using compartment models. Specifically, a general mathematical model is developed for the dynamic behavior of a multicompartment respiratory system. Then, based on this multicompartment model, an optimal respiratory pattern is characterized using classical calculus of variations minimization techniques for inspiratory and expiratory breathing cycles. Furthermore, model predictive controller frameworks are designed to track the given optimal respiratory air flow pattern while satisfying control input amplitude and rate constrains.
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Bonis, Ioannis. "Optimisation and control methodologies for large-scale and multi-scale systems." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/optimisation-and-control-methodologies-for-largescale-and-multiscale-systems(6c4a4f13-ebae-4d9d-95b7-cca754968d47).html.
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Distributed parameter systems (DPS) comprise an important class of engineering systems ranging from "traditional" such as tubular reactors, to cutting edge processes such as nano-scale coatings. DPS have been studied extensively and significant advances have been noted, enabling their accurate simulation. To this end a variety of tools have been developed. However, extending these advances for systems design is not a trivial task . Rigorous design and operation policies entail systematic procedures for optimisation and control. These tasks are "upper-level" and utilize existing models and simulators. The higher the accuracy of the underlying models, the more the design procedure benefits. However, employing such models in the context of conventional algorithms may lead to inefficient formulations. The optimisation and control of DPS is a challenging task. These systems are typically discretised over a computational mesh, leading to large-scale problems. Handling the resulting large-scale systems may prove to be an intimidating task and requires special methodologies. Furthermore, it is often the case that the underlying physical phenomena span various temporal and spatial scales, thus complicating the analysis. Stiffness may also potentially be exhibited in the (nonlinear) models of such phenomena. The objective of this work is to design reliable and practical procedures for the optimisation and control of DPS. It has been observed in many systems of engineering interest that although they are described by infinite-dimensional Partial Differential Equations (PDEs) resulting in large discretisation problems, their behaviour has a finite number of significant components , as a result of their dissipative nature. This property has been exploited in various systematic model reduction techniques. Of key importance in this work is the identification of a low-dimensional dominant subspace for the system. This subspace is heuristically found to correspond to part of the eigenspectrum of the system and can therefore be identified efficiently using iterative matrix-free techniques. In this light, only low-dimensional Jacobians and Hessian matrices are involved in the formulation of the proposed algorithms, which are projections of the original matrices onto appropriate low-dimensional subspaces, computed efficiently with directional perturbations.The optimisation algorithm presented employs a 2-step projection scheme, firstly onto the dominant subspace of the system (corresponding to the right-most eigenvalues of the linearised system) and secondly onto the subspace of decision variables. This algorithm is inspired by reduced Hessian Sequential Quadratic Programming methods and therefore locates a local optimum of the nonlinear programming problem given by solving a sequence of reduced quadratic programming (QP) subproblems . This optimisation algorithm is appropriate for systems with a relatively small number of decision variables. Inequality constraints can be accommodated following a penalty-based strategy which aggregates all constraints using an appropriate function , or by employing a partial reduction technique in which only equality constraints are considered for the reduction and the inequalities are linearised and passed on to the QP subproblem . The control algorithm presented is based on the online adaptive construction of low-order linear models used in the context of a linear Model Predictive Control (MPC) algorithm , in which the discrete-time state-space model is recomputed at every sampling time in a receding horizon fashion. Successive linearisation around the current state on the closed-loop trajectory is combined with model reduction, resulting in an efficient procedure for the computation of reduced linearised models, projected onto the dominant subspace of the system. In this case, this subspace corresponds to the eigenvalues of largest magnitude of the discretised dynamical system. Control actions are computed from low-order QP problems solved efficiently online.The optimisation and control algorithms presented may employ input/output simulators (such as commercial packages) extending their use to upper-level tasks. They are also suitable for systems governed by microscopic rules, the equations of which do not exist in closed form. Illustrative case studies are presented, based on tubular reactor models, which exhibit rich parametric behaviour.
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Havlíček, Martin. "Zkoumání konektivity mozkových sítí pomocí hemodynamického modelování." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233576.
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Zobrazení funkční magnetickou rezonancí (fMRI) využívající "blood-oxygen-level-dependent" efekt jako indikátor lokální aktivity je velmi užitečnou technikou k identifikaci oblastí mozku, které jsou aktivní během percepce, kognice, akce, ale také během klidového stavu. V poslední době také roste zájem o studium konektivity mezi těmito oblastmi, zejména v klidovém stavu. Tato práce předkládá nový a originální přístup k problému nepřímého vztahu mezi měřenou hemodynamickou odezvou a její příčinou, tj. neuronálním signálem. Zmíněný nepřímý vztah komplikuje odhad efektivní konektivity (kauzálního ovlivnění) mezi různými oblastmi mozku z dat fMRI. Novost prezentovaného přístupu spočívá v použití (zobecněné nelineární) techniky slepé dekonvoluce, což dovoluje odhad endogenních neuronálních signálů (tj. vstupů systému) z naměřených hemodynamických odezev (tj. výstupů systému). To znamená, že metoda umožňuje "data-driven" hodnocení efektivní konektivity na neuronální úrovni i v případě, že jsou měřeny pouze zašumělé hemodynamické odezvy. Řešení tohoto obtížného dekonvolučního (inverzního) problému je dosaženo za použití techniky nelineárního rekurzivního Bayesovského odhadu, který poskytuje společný odhad neznámých stavů a parametrů modelu. Práce je rozdělena do tří hlavních částí. První část navrhuje metodu k řešení výše uvedeného problému. Metoda využívá odmocninové formy nelineárního kubaturního Kalmanova filtru a kubaturního Rauch-Tung-Striebelova vyhlazovače, ovšem rozšířených pro účely řešení tzv. problému společného odhadu, který je definován jako simultánní odhad stavů a parametrů sekvenčním přístupem. Metoda je navržena především pro spojitě-diskrétní systémy a dosahuje přesného a stabilního řešení diskretizace modelu kombinací nelineárního (kubaturního) filtru s metodou lokální linearizace. Tato inverzní metoda je navíc doplněna adaptivním odhadem statistiky šumu měření a šumů procesu (tj. šumů neznámých stavů a parametrů). První část práce je zaměřena na inverzi modelu pouze jednoho časového průběhu; tj. na odhad neuronální aktivity z fMRI signálu. Druhá část generalizuje navrhovaný přístup a aplikuje jej na více časových průběhů za účelem umožnění odhadu parametrů propojení neuronálního modelu interakce; tj. odhadu efektivní konektivity. Tato metoda představuje inovační stochastické pojetí dynamického kauzálního modelování, což ji činí odlišnou od dříve představených přístupů. Druhá část se rovněž zabývá metodami Bayesovského výběru modelu a navrhuje techniku pro detekci irelevantních parametrů propojení za účelem dosažení zlepšeného odhadu parametrů. Konečně třetí část se věnuje ověření navrhovaného přístupu s využitím jak simulovaných tak empirických fMRI dat, a je významných důkazem o velmi uspokojivých výsledcích navrhovaného přístupu.
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Choi, Jinbae. "Closed-Loop Optimal Control of Discrete-Time Multiple Model Linear Systems with Unknown Parameters." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1441178373.
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Afri, Chouaib. "Observateurs adaptatifs pour l'identification en ligne et l'observation des systèmes linéaires." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1302/document.
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Dans cette thèse, nous étudions le problème de l'identification d'un système à dynamique linéaire. Dans un premier temps, nous répertorions les différentes méthodes qui ont été développées dans la littérature en nous concentrant plus particulièrement sur les méthodes des observateurs adaptatifs. Dans un second temps nous présentons un premier algorithme qui est une approche mixant les méthodes des sous-espaces et celles des observateurs adaptatifs. Ce nouvel algorithme est d'autant plus intéressant qu'il nous permet d'identifier des réalisations de systèmes MIMO dans une base d'état arbitraire. La convergence de cet algorithme est démontrée en utilisant les notions d'excitation persistantes. Dans un troisième chapitre nous introduisons une nouvelle méthode qui s'appuie sur le concept des observateurs de Luenberger non linéaires développés ces dernières années. Ce nouvel algorithme se différencie des algorithmes existants par sa capacité à produire une estimation simultanée des paramètres et de l'état du système. Nous démontrons alors sa robustesse à des perturbations affectant la dynamique interne ou les mesures. La convergence de cet algorithme est obtenue si les entrées du système satisfont une hypothèse d'excitation différentielle. Tous ces algorithmes sont alors évalués et implémentés sur un banc d'expérimentationIn this thesis, we study the problem of identification of a linear dynamical system. First, we survey various methods that have been developed in the literature. We focus more particularly on methods named adaptive observers. Secondly we present an approach which combines subspace identification methods and adaptive observers. This new method is interesting since it allows us to identify MIMO systems in an arbitrary basis. The convergence of this algorithm is demonstrated using the persistent excitation notions. In the third chapter we introduce a new method that is inspired from nonlinear Luenberger observers developed in recent years. This new algorithm is different from the existing algorithms since the parameters and the systemstatus are estimated simultaneously. We demonstrate the robustness of this approach. The convergence of the algorithm is obtained if the system inputs satisfy a differential excitation hypothesis. All these algorithms are evaluated and implemented on an experimental bench
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Mehmood, Adeel. "Modeling, simulation and robust control of an electro-pneumatic actuator for a variable geometry turbocharger." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2012. http://tel.archives-ouvertes.fr/tel-00827445.
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The choice of technology for automotive actuators is driven by the need of high power to size ratio. In general, electro-pneumatic actuators are preferred for application around the engine as they are compact, powerful and require simple controlling devices. Specially, Variable Geometry Turbochargers (VGTs) are almost always controlled with electro-pneumatic actuators. This is a challenging application because the VGT is an important part of the engine air path and the latter is responsible for intake and exhaust air quality and exhaust emissions control. With government regulations on vehicle pollutant emissions getting stringent by the year, VGT control requirements have also increased. These regulations and requirements can only be fulfilled with precise dynamic control of the VGT through its actuator. The demands on actuator control include robustness against uncertainty in operating conditions, fast and smooth positioning without vibration, limited number of measurements. Added constraints such as nonlinear dynamic behavior of the actuator, friction and varying aerodynamic forces in the VGT render classical control methods ineffective. These are the main problems that form the core of this thesis.In this work, we have addressed the above mentioned problems, using model based control complemented with robust control methods to overcome operational uncertainties and parametric variations. In the first step, a detailed physical model of an electro-pneumatic actuator has been developed; taking into account the nonlinear characteristics originating from air compressibility and friction. Means to compensate for aerodynamic force have been studied and implemented in the next step. These include model parametric adaptation and one dimensional CFD (Computational Fluid Dynamics) modeling. The complete model has been experimentally validated and a sensitivity analysis has been conducted to identify the parameters which have the greatest impact upon the actuator's behavior. The detailed simulation model has then been simplified to make it suitable for control purposes while keeping its essential behavioral characteristics (i.e. transients and dynamics). Next, robust controllers have been developed around the model for the control objective of accurate actuator positioning in presence of operational uncertainty. An important constraint in commercial actuators is that they provide output feedback only, as they are only equipped with low-cost position sensors. This hurdle has been overcome by introducing observers in the control loop, which estimate other system states from the output feedback. The estimation and control algorithms have been validated in simulation and experimentally on diesel engine test benches.
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Nasri, Imed. "Développement d'une méthodologie d'ordonnancement/optimisation adaptée aux systèmes industriels de type HVLV (High-Variety, Low-Volume)." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00831002.
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Les travaux présentés dans cette thèse portent sur la conception d'une méthodologie d'ordonnancement/optimisation pour les systèmes de production à grande variété de produits et faible densité de flux appelés systèmes HVLV (High-Variety, LowVolume). Les caractéristiques de ces systèmes nous permettent d'appréhender la représentation des flux y circulant par un modèle discret. Le comportement discontinu des systèmes HVLV peut être caractérisé par la connaissance des dates de début et de fin des activités de production. L'algèbre (max, +) est utilisée pour représenter ce type de systèmes où les relations entre les dates de début des activités nécessitent l'utilisation des opérateurs maximum et addition. Afin d'utiliser l'algèbre (max, +) pour l'ordonnancement des systèmes HVLV, il est indispensable de résoudre un problème de conflit et d'optimisation sous contraintes dans cette algèbre. D'abord, nous avons développé dans ces travaux de recherche un modèle d'ordonnancement (max, +) pour les systèmes HVLV dans lequel des variables de décision ont été introduites afin de résoudre le problème de conflit entre les opérations exécutées sur les machines. Ensuite, nous avons amélioré le modèle proposé pour tenir compte de la maintenance préventive. Deux types de maintenance ont été considérés : Maintenance Périodique Répétitive (MPR) et Maintenance Flexible Périodique (MFP). Dans les deux cas, un problème d'ordonnancement non-linéaire sous contraintes a été résolu afin de minimiser certains critères de performance. Enfin, la méthodologie proposée a été validée par simulation, sur des systèmes HVLV complexes de type job-shop.
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Dimassi, Habib. "Synchronisation des systèmes chaotiques par observateurs et applications à la transmission d'informations." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00856590.
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Dans ce travail de thèse, nous développons des méthodes de synchronisation des systèmes chaotiques pour les applications de transmission d'informations. La première méthode de synchronisation que nous proposons est basée sur les observateurs adaptatifs à entrées inconnues pour une classe des systèmes chaotiques présentant des incertitudes paramétriques et des perturbations dans leurs dynamiques et du bruit dans les signaux de sortie (bruit dans le canal de communication). La méthode développée repose sur les techniques adaptatives pour la compensation des non-linéarités et des incertitudes paramétriques et pour la restauration des messages transmis. Elle se base également sur les méthodes de synthèse d'observateurs à entrées inconnues pour supprimer l'influence des perturbations et du bruit. Ensuite, nous développons une deuxième méthode de synchronisation utilisant un observateur adaptatif à ''modes glissants" pour une classe des systèmes chaotiques présentant des entrées inconnues et dont les signaux de sortie sont bruités. La synthèse de l'observateur s'appuie sur la théorie des modes glissants, les techniques de synthèse d'observateurs singuliers et les techniques adaptatives dans le but d'estimer conjointement l'état et les entrées inconnues malgré la présence du bruit dans les équations de sortie. Cette approche de synchronisation est ensuite employée dans un nouveau schéma de communication chaotique sécurisée dont l'objectif est d'augmenter le nombre et l'amplitude des messages transmis, améliorer le niveau de sécurité ainsi que la robustesse aux bruits présents dans le canal de communication. En outre, le scénario de présence des retards de transmission est étudié en élaborant une troisième approche de synchronisation à base d'observateurs adaptatifs pour une classe des systèmes chaotiques de Lur'e avec des non-linéarités à pente restreinte et des signaux de sortie retardés. En se basant sur la théorie de Lyapunov-Krasovskii et en utilisant une hypothèse d'excitation persistante, l'observateur adaptatif proposé garantit la synchronisation maitre-esclave et la restauration des informations transmises malgré l'existence des retards de transmission. Les résultats théoriques obtenus dans ce travail de thèse sont vérifiés à travers des applications de transmission d'informations utilisant différents modèles des systèmes chaotiques tout en étudiant les différents scénarios et cas de figure pouvant se présenter en pratique et en analysant les aspects de sécurité de ces systèmes.
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Eichwald, Brice. "Intégrateurs exponentiels modifiés pour la simulation des vagues non linéaires." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00873578.
Full textAbstract:
Pour réaliser des simulations précises aux temps longs pour des vagues non linéaires, il faut faire appel à des algorithmes d'évolution temporelle précis. En particulier, la combinaison d'un pas de temps adaptatif avec un facteur intégrant est connue pour être très efficace. Nous proposons une modification de cette technique. Le principe consiste à soustraire un certain polynôme à une EDP. Puis, comme pour le facteur intégrant, nous faisons un changement de variable pour retirer la partie linéaire. Mais nous espérons retirer quelque chose de plus afin de rendre l'EDP moins raide pour les calculs numériques. Le polynôme choisi est une expansion de Taylor autour du temps initial de la solution. Afin de calculer les différentes dérivées nécessaires, nous utilisons le Dense Output qui donne la possibilité d'approximer les dérivées de la solution à tout temps. Une fois le facteur intégrant modifié appliqué, nous faisons appel à une avance temporelle classique afin de résoudre l'équation d'évolution. Il a été considéré plusieurs schémas de Runge-Kutta avec pas de temps adaptatif. Nous avons tiré avantage des méthodes emboîtées, afin de ne pas calculer de nouvelles fonctions et perdre du temps de calcul, en utilisant uniquement des données déjà calculées durant l'évolution temporelle. Les résultats numériques montrent que l'efficacité de notre méthode varie selon les cas. Par exemple, nous avons vérifié que plus le profil de l'onde est pentue, plus notre méthode est efficace. Pour le modèle de vagues non linéaires le plus compliqué à notre disposition, le modèle HOS, nous avons pu réduire le nombre de pas de temps de calcul jusqu'à près de 30 % avec un schéma de Runge-Kutta de Dormand-Prince et jusqu'à plus de 99 % pour un schéma de Bogacki-Shampine.
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Sklar, Alexander Gabriel. "Channel Modeling Applied to Robust Automatic Speech Recognition." Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_theses/87.
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In automatic speech recognition systems (ASRs), training is a critical phase to the system?s success. Communication media, either analog (such as analog landline phones) or digital (VoIP) distort the speaker?s speech signal often in very complex ways: linear distortion occurs in all channels, either in the magnitude or phase spectrum. Non-linear but time-invariant distortion will always appear in all real systems. In digital systems we also have network effects which will produce packet losses and delays and repeated packets. Finally, one cannot really assert what path a signal will take, and so having error or distortion in between is almost a certainty. The channel introduces an acoustical mismatch between the speaker's signal and the trained data in the ASR, which results in poor recognition performance. The approach so far, has been to try to undo the havoc produced by the channels, i.e. compensate for the channel's behavior. In this thesis, we try to characterize the effects of different transmission media and use that as an inexpensive and repeatable way to train ASR systems.
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Khlaief, Amor. "Contribution à la commande vectorielle sans capteur mécanique des machines synchrones à aimants permanents (MSAP)." Phd thesis, Aix-Marseille Université, 2012. http://tel.archives-ouvertes.fr/tel-00814276.
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Ce travail de recherche s'intéresse à la commande sans capteur mécanique du moteur synchrone à aimants permanents (MSAP) à pôles saillants, particulièrement en basse vitesse, avec détection de la position initiale du rotor. Après une présentation des techniques et approches qui ont initié nos travaux, en terme d'estimation de la vitesse et/ou de la position, nous avons choisi celles qui présentent plus d'intérêt de point de vue stabilité, robustesse, précision et simplicité d'implémentation. La première approche est basée sur le Système Adaptatif avec Modèle de Référence (MRAS). Quant à la deuxième, elle est réalisée autour d'un observateur non-linéaire pour l'estimation de la position et de la vitesse du MSAP à pôles saillants. Les deux techniques d'observation de la vitesse sont associées à une commande par orientation du flux rotorique avec la technique MLI vectorielle. Pour détecter la position initiale du rotor, nous avons utilisé une nouvelle approche qui permet d'estimer cette position avec une incertitude de 5° mécanique. Cette nouvelle approche est basée sur l'application de signaux tests aux bornes des phases statoriques du MSAP. Des résultats de simulation et expérimentaux sont présentés tout au long de ces travaux pour valider les études théoriques de la commande vectorielle sans capteur mécanique du MSAP. Enfin, nous avons étudié et analysé les performances de la commande tolérante aux défauts sans capteur mécanique du MSAP en présence de défaillances de types transistors à l'état-off. Les résultats expérimentaux obtenus avec les deux approches d'estimation de la vitesse en utilisant l'observateur MRAS et un observateur non linéaire ont permis d'améliorer la fiabilité du système de manière à rendre possible la commande vectorielle sans capteur mécanique en mode dégradé (alimentation avec deux bras de l'onduleur). En effet, les résultats de la commande sans capteur mécanique de la MSAP en mode dégradé montrent que l'observateur non linéaire est le mieux adapté pour ce type de fonctionnement car il présente de faible ondulation du couple et de vitesse. A l'aide d'un banc d'essais que nous avons développé au laboratoire LSIS-pôle Ecole Centrale de Marseille (ECM), nous avons pu valider expérimentalement les différentes approches proposées dans ce travail de recherche. Les résultats obtenus montrent l'efficacité des techniques mises en œuvre pour la commande vectorielle sans capteur mécanique du MSAP à pôle saillant en termes de robustesse, stabilité, précision et rapidité.
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"Stabilization and regulation of nonlinear systems with applications: robust and adaptive approach." Thesis, 2008. http://library.cuhk.edu.hk/record=b6074684.
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Despite the fact that significant progress has been made on the research of these two problems for nonlinear systems for over two decades, many problems are still open. In particular, so far the output regulation problem is mainly handled by robust control approach. This approach has certain fundamental limitations and cannot handle the following three cases. (1) The control direction is unknown. (2) The boundaries of system uncertainties are unknown. (3) The exosystem is not known precisely.Stabilization and output regulation are two fundamental control problems. The output regulation problem aims to design a feedback controller to achieve asymptotic tracking of a class of reference inputs and rejection of a class of disturbances in an uncertain system while maintaining the internal stability of the closed-loop system. Thus the output regulation problem is more demanding than the stabilization problem. Nevertheless, under some assumptions, the output regulation problem can be converted into a stabilization problem for a well defined augmented system and the solvability of the stabilization problem for this augmented system implies that of the output regulation problem for the original plant. Therefore, to a large extent, the study of the stabilization problem will also lay a foundation for that of the output regulation problem.
To handle these problems and overcome the shortcomings of the robust control approach, in this thesis, we have incorporated the adaptive control approach with the robust control approach. Both stabilization problem and output regulation problem are considered for two important classes of nonlinear systems, namely, the output feedback systems and lower triangular systems. The main contributions are summarized as follows. (1) The adaptive output regulation problem for nonlinear systems in output feedback form is addressed without knowing the control direction. The Nussbaum gain technique is incorporated with the robust control technique to handle the unknown control direction and the nonlinearly parameterized uncertainties in the system. To overcome the dilemma caused by the unknown control direction and the nonlinearly parameterized uncertainties, we have adopted a Lyapunov direct method to solve the adaptive output regulation problem. (2) The adaptive stabilization problem for nonlinear systems in lower triangular form is solved when both static and dynamic uncertainties are present and the control direction is unknown. Technically, the presence of dynamic uncertainty has made the stabilization problem more difficult than the previous work. We have managed to combine the changing supply rate technique and the Nussbaum gain technique to deal with this difficulty. The result is also applied to solve the output regulation problem for lower triangular systems with unknown control direction. (3) The adaptive output regulation problem for nonlinear systems in output feed-back form with unknown exosystem is studied. The adaptive control technique is applied to estimate the unknown parameter results from the unknown exosystem. The condition under which the parameter estimation converges to its real value is also discussed. Further, the global disturbance rejection problem for nonlinear systems in lower triangular form is solved by formulating the unknown external disturbance as a signal produced by an unknown exosystem. (4) The theoretical results have been applied to several typical control systems leading to the solution of some long standing open problems. Some exemplified applications are: (a) Global adaptive stabilization of Chua's circuit without knowing the control direction; (b) Global output synchronization of the Chua's circuit and the harmonic system; (c) Global adaptive disturbance rejection problem of the Duffing's system with all parameters unknown; (d) Global adaptive output regulation of Van der Pol oscillator with an uncertain exosystem.
Liu, Lu.
Adviser: Jie Huang.
Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3693.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references (leaves 204-214).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
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Wang, Qingqing. "Robust adaptive controls of nonlinear systems with actuator hysteresis represented by Prandtl-Ishlinskii models." Thesis, 2006. http://spectrum.library.concordia.ca/9239/1/wang_qingqing_2006.pdf.
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The development of control techniques to mitigate the effects of unknown hysteresis preceding with plants, has recently re-attracted significant attention. This thesis deals with robust adaptive control of nonlinear systems preceded by unknown hysteresis nonlinearities. In the literature, the most common methods to reduce hysteresis effects to the controlled systems are based on the inverse hysteresis compensations. Due to the complexity of hysteresis behavior, this approach has its limit. By thoroughly investigating the Prandtl-Ishlinskii models of hysteresis, a robust adaptive control scheme was developed, which makes it possible to fuse the model of hysteresis with the available control techniques without necessarily constructing a hysteresis inverse. The global stability of the adaptive system and to track a desired trajectory to a certain precision are achieved. Two classes of nonlinear systems preceded by unknown hysteresis nonlinearities are studied. One class of systems is with parametric uncertainties and known nonlinear functions. By integrating proposed hysteresis adaptation law with sliding mode control and back-stepping techniques, the global stability and tracking a desired trajectory to a certain precision are achieved. Simulation results attained for an example of this class of nonlinear system are presented to illustrate and further validate the effectiveness of the proposed approaches. Then the approach is extended to a more general class of systems in the presence of parametric uncertainties and unknown nonlinear functions with bounded disturbances and preceded by unknown hysteresis nonlinearities. Combined with neural networks adaptation control method, it is proved that for any bounded initial conditions, all closed-loop signals are bounded and the state vector x ( t ) converges to a neighborhood of the desired trajectory. Concerning the practical applications, determination of the density function of the Prandtl-Ishlinskii model is crucial. In this study, a discretional approach is developed to approximate density function p ( r ) based on the memory effects of the play operator F r [ v ]( t )
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Bean, Ronnie A. "Nonlinear control of high performance aircraft." Thesis, 1994. http://hdl.handle.net/1957/35260.
Full textAbstract:
This thesis presents the design of various controllers for a highly maneuverable,
high performance aircraft, namely the modified F-18. The aircraft
was required to perform high angle-of-attack maneuvers, for which the aircraft
behaves in as a highly nonlinear system. An adaptive PID controller
was used to control the aircraft through these high angle-of-attack maneuvers.
Several nonlinear controllers were then developed based on the adaptive PID
control, and were tested for robustness. This thesis also looks at an improvement
in the aircraft which may improve performance in high angle-of-attack
maneuvers.
The contributions of this thesis are in the areas of control, in general, and
specifically in the area of aircraft control. Successful application of linear
adaptive control and nonlinear control were presented. In the area of aircraft
control, controllers were presented which produce good performance for high
angle-of-attack maneuvers, while maintaining implementability. Also, some
insight is gained into what aircraft changes could improve performance.Graduation date: 1995
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Mishra, Bijoyananda. "Growth of value added services in Indian telecom industry: a diagnostic study." Thesis, 2018. http://eprint.iitd.ac.in:80//handle/2074/7938.
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Ker, Shi-Hao, and 柯世豪. "On-Line Intelligent Adaptive Control for Uncertain Nonlinear Systems using Optimally Trained TS-Type Fuzzy Models." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/40723179731965306468.
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碩士國立交通大學
電機與控制工程系
90
A new approach for on-line intelligent indirect adaptive control of uncertain nonlinear systems is explored in this thesis using optimally trained Takagi-Sugeno (TS)-type fuzzy models. It is a common practice to assume that the uncertain nonlinear system can possess a linearized TS-type fuzzy model at any time instant. The linearized TS-type fuzzy model should be different at different time instants. The dynamical optimal learning rule can be adopted to update the linearized TS-type fuzzy model to guarantee the convergence of on-line training process. Also the initialization of the linearized TS-type fuzzy model is very important to speed-up the convergence rate. This will be based on the least-squared identification. It must be emphasized that once the linearized TS-type fuzzy model of the uncertain nonlinear system is obtained in real-time environment, the on-line adaptive controller can be easily designed to accomplish the design specifications, i.e., stabilizing the unknown nonlinear system, tracking of a reference signal, …, etc. A simplified tracking controller is also proposed to perform the tracking of a reference signal for the unknown nonlinear system. Two nonlinear systems, i.e., mass-spring-damper, inverted pendulum system, and Chua’s chaotic circuit are fully illustrated to track sinusoidal signals. The resulting on-line indirect adaptive controller shows excellent results.
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Sidhu, Amardeep Singh. "Fault diagnosis of lithium ion battery using multiple model adaptive estimation." Thesis, 2013. http://hdl.handle.net/1805/4447.
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Indiana University-Purdue University Indianapolis (IUPUI)Lithium ion (Li-ion) batteries have become integral parts of our lives; they are widely used in applications like handheld consumer products, automotive systems, and power tools among others. To extract maximum output from a Li-ion battery under optimal conditions it is imperative to have access to the state of the battery under every operating condition. Faults occurring in the battery when left unchecked can lead to irreversible, and under extreme conditions, catastrophic damage. In this thesis, an adaptive fault diagnosis technique is developed for Li-ion batteries. For the purpose of fault diagnosis the battery is modeled by using lumped electrical elements under the equivalent circuit paradigm. The model takes into account much of the electro-chemical phenomenon while keeping the computational effort at the minimum. The diagnosis process consists of multiple models representing the various conditions of the battery. A bank of observers is used to estimate the output of each model; the estimated output is compared with the measurement for generating residual signals. These residuals are then used in the multiple model adaptive estimation (MMAE) technique for generating probabilities and for detecting the signature faults. The effectiveness of the fault detection and identification process is also dependent on the model uncertainties caused by the battery modeling process. The diagnosis performance is compared for both the linear and nonlinear battery models. The non-linear battery model better captures the actual system dynamics and results in considerable improvement and hence robust battery fault diagnosis in real time. Furthermore, it is shown that the non-linear battery model enables precise battery condition monitoring in different degrees of over-discharge.
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Su, Tai-Ming, and 蘇泰銘. "Design of Model Reference Adaptive Tracking Controllers for Mismatch Perturbed Nonlinear Systems with Nonlinear Inputs." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/16791391565580318054.
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碩士國立中山大學
電機工程學系研究所
92
A simple design methodology of optimal model reference adaptive control (OMRAC) scheme with perturbation estimation for solving robust tracking problems is proposed in this thesis. The plant to be controlled belongs to a class of MIMO perturbed dynamic systems with input nonlinearity and time varying delay. The proposed robust tracking controller with a perturbation estimation scheme embedded is designed by using Lyapunov stability theorem. The control scheme contains three types of controllers. The first one is a linear feedback optimal controller, which is designed under the condition that no perturbation exists. The second one is an adaptive controller, it is used for adapting the unknown upper bound of perturbation estimation error. The third one is the perturbation estimation mechanism. The property of uniformly ultimately boundness is proved under the proposed control scheme, and the effects of each design parameter on the dynamic performance is also analyzed. An example is demonstrated for showing the feasibility of the proposed control scheme.
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Chiu-Hsiung, Chen. "Adaptive Robust Cerebellar Model Articulation Controller Design for Uncertain Nonlinear Systems." 2007. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-2901200723001300.
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SONG, ZHEN-TAN, and 宋真坦. "The analysis of model reference adaptive control for certain nonlinear systems." Thesis, 1987. http://ndltd.ncl.edu.tw/handle/14661135647524630336.
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