Дисертації з теми "Nonlinear adaptive models"
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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.
Повний текст джерелаAdam, 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.
Повний текст джерелаMcCallum, 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.
Повний текст джерелаCERBONI, BAIARDI LORENZO. "Adaptive models of learning in complex physical and social systems." Doctoral thesis, Urbino, 2016. http://hdl.handle.net/11576/2630552.
Повний текст джерелаMazumdar, 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.
Повний текст джерелаTon, 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.
Повний текст джерелаEckardt, 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.
Повний текст джерелаStrömberg, 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.
Повний текст джерелаMinggao, Wei. "Human Head Stiffness Rendering." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32743.
Повний текст джерелаMANICKAM, NITHYA. "NONLINEAR AND ADAPTIVE CONTROL OF MODEL HELICOPTER." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1144639875.
Повний текст джерелаNigro, 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/.
Повний текст джерелаA 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.
Lopez, Brett Thomas. "Adaptive robust model predictive control for nonlinear systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122395.
Повний текст джерелаCataloged 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
CASSARO, MARIO. "Model Reference Adaptive Control Laws: Application to Nonlinear Aeroelastic Systems." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2605774.
Повний текст джерелаDavenport, James Michael. "An Adaptive Dose Finding Design (DOSEFIND) Using A Nonlinear Dose Response Model." VCU Scholars Compass, 2007. http://hdl.handle.net/10156/13.
Повний текст джерелаBohn, 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.
Повний текст джерелаGaunersdorfer, 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.
Повний текст джерелаSeries: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
Yang, Shu. "Modeling and Control of Tensegrity-Membrane Systems." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71686.
Повний текст джерелаPh. D.
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.
Повний текст джерелаGunbatar, 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаZhang, Cheng. "A contribution to the nonlinear control of floating wind turbines." Thesis, Ecole centrale de Nantes, 2021. http://www.theses.fr/2021ECDN0009.
Повний текст джерелаFloating 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
KARIMSHOUSHTARI, MILAD. "Design of Experiments for Nonlinear System Identification." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2751496.
Повний текст джерелаZhang, Huaiye. "Bayesian Approach Dealing with Mixture Model Problems." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/37681.
Повний текст джерелаPh. D.
Jaramillo, López Fernando. "Control and Model Identification on Renewable Energy Systems." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112240.
Повний текст джерелаThe 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
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.
Повний текст джерелаDavidson, 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.
Повний текст джерелаNguyen, 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.
Повний текст джерелаPh. D.
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.
Повний текст джерелаYan, Xinming. "Development of robust control based on sliding mode for nonlinear uncertain systems." Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0012.
Повний текст джерелаThis 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
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.
Повний текст джерелаLi, Hancao. "Modeling and control of a pressure-limited respirator and lung mechanics." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47667.
Повний текст джерелаBonis, 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.
Повний текст джерелаHavlíček, 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.
Повний текст джерелаChoi, 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.
Повний текст джерелаAfri, Chouaib. "Observateurs adaptatifs pour l'identification en ligne et l'observation des systèmes linéaires." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1302/document.
Повний текст джерелаIn 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
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.
Повний текст джерелаNasri, 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.
Повний текст джерелаDimassi, 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.
Повний текст джерелаEichwald, 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.
Повний текст джерелаSklar, Alexander Gabriel. "Channel Modeling Applied to Robust Automatic Speech Recognition." Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_theses/87.
Повний текст джерелаKhlaief, 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.
Повний текст джерела"Stabilization and regulation of nonlinear systems with applications: robust and adaptive approach." Thesis, 2008. http://library.cuhk.edu.hk/record=b6074684.
Повний текст джерелаStabilization 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.
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.
Повний текст джерелаBean, Ronnie A. "Nonlinear control of high performance aircraft." Thesis, 1994. http://hdl.handle.net/1957/35260.
Повний текст джерелаGraduation date: 1995
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.
Повний текст джерелаKer, 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.
Повний текст джерела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.
Sidhu, Amardeep Singh. "Fault diagnosis of lithium ion battery using multiple model adaptive estimation." Thesis, 2013. http://hdl.handle.net/1805/4447.
Повний текст джерелаLithium 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.
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.
Повний текст джерела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.
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.
Повний текст джерелаSONG, 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.
Повний текст джерела