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Data Driven Nonparametric Adaptive Control Theory

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Data Driven Nonparametric Adaptive Control Theory

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Author : Andrew J. Kurdila
language : en
Publisher:
Release Date : 2025-04-12

Data Driven Nonparametric Adaptive Control Theory written by Andrew J. Kurdila and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-12 with Language Arts & Disciplines categories.

Data Driven Nonparametric Adaptive Control Theory

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Author : Andrew J. Kurdila
language : en
Publisher: Springer Nature
Release Date : 2025-05-10

Data Driven Nonparametric Adaptive Control Theory written by Andrew J. Kurdila and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-10 with Science categories.

Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties. The methods proposed enforce satisfactory trajectory tracking despite functional uncertainties in the plant model. The book employs the properties of reproducing kernel Hilbert (native) spaces to characterize both the functional space of uncertainties and the controller's performance. Classical control systems are extended to broader classes of problems and more informative characterizations of the controllers’ performances are attained. Following an examination of how backstepping control and robust control Lyapunov functions can be ported to the native setting, numerous extensions of the model reference adaptive control framework are considered. The authors’ approach breaks away from classical paradigms in which uncertain nonlinearities are parameterized using a regressor vector provided a priori or reconstructed online. The problem of distributing the kernel functions that characterize the native space is addressed at length by employing data-driven methods in deterministic and stochastic settings. The first part of this book is a self-contained resource, systematically presenting elements of real analysis, functional analysis, and native space theory. The second part is an exposition of the theory of nonparametric control systems design. The text may be used as a self-study book for researchers and practitioners and as a reference for graduate courses in advanced control systems design. MATLAB® codes, available on the authors’ website, and suggestions for homework assignments help readers appreciate the implementation of the theoretical results.

Model Free Adaptive Control

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Author : Zhongsheng Hou
language : en
Publisher: CRC Press
Release Date : 2013-09-24

Model Free Adaptive Control written by Zhongsheng Hou and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-24 with Computers categories.

Data Driven Model Free Controllers

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Author : Radu-Emil Precup
language : en
Publisher: CRC Press
Release Date : 2021-12-26

Data Driven Model Free Controllers written by Radu-Emil Precup and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-26 with Technology & Engineering categories.

This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model‐free and model‐free adaptive‐Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.

Continuous Optimization And Variational Inequalities

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Author : Anurag Jayswal
language : en
Publisher: CRC Press
Release Date : 2022-09-13

Continuous Optimization And Variational Inequalities written by Anurag Jayswal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-13 with Technology & Engineering categories.

The proposed book provides a comprehensive coverage of theory and methods in the areas of continuous optimization and variational inequality. It describes theory and solution methods for optimization with smooth and non-smooth functions, for variational inequalities with single-valued and multivalued mappings, and for related classes such as mixed variational inequalities, complementarity problems, and general equilibrium problems. The emphasis is made on revealing generic properties of these problems that allow creation of efficient solution methods. Salient Features The book presents a deep, wide-ranging introduction to the theory of the optimal control of processes governed by optimization techniques and variational inequality Several solution methods are provided which will help the reader to develop various optimization tools for real-life problems which can be modeled by optimization techniques involving linear and nonlinear functions. The book focuses on most recent contributions in the nonlinear phenomena, which can appear in various areas of human activities. This book also presents relevant mathematics clearly and simply to help solve real life problems in diverse fields such as mechanical engineering, management, control behavior, traffic signal, industry, etc. This book is aimed primarily at advanced undergraduates and graduate students pursuing computer engineering and electrical engineering courses. Researchers, academicians and industry people will also find this book useful.

Advances In Guidance Navigation And Control

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Author : Liang Yan
language : en
Publisher: Springer Nature
Release Date : 2023-02-10

Advances In Guidance Navigation And Control written by Liang Yan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-10 with Technology & Engineering categories.

This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

Discrete Time Adaptive Iterative Learning Control

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Author : Ronghu Chi
language : en
Publisher: Springer Nature
Release Date : 2022-03-21

Discrete Time Adaptive Iterative Learning Control written by Ronghu Chi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-21 with Technology & Engineering categories.

This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.

Parameter Estimation And Adaptive Control For Nonlinear Servo Systems

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Author : Shubo Wang
language : en
Publisher: Elsevier
Release Date : 2024-01-16

Parameter Estimation And Adaptive Control For Nonlinear Servo Systems written by Shubo Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-16 with Technology & Engineering categories.

Parameter Estimation and Adaptive Control for Nonlinear Servo Systems presents the latest advances in observer-based control design, focusing on adaptive control for nonlinear systems such as adaptive neural network control, adaptive parameter estimation, and system identification. This book offers an array of new real-world applications in the field. Written by eminent scientists in the field of control theory, this book covers the latest advances in observer-based control design. It provides fundamentals, algorithms, and it discusses key applications in the fields of power systems, robotics and mechatronics, flight and automotive systems. - Presents a clear and concise introduction to the latest advances in parameter estimation and adaptive control with several concise applications for servo systems - Covers a wide range of applications usually not found in similar books, such as power systems, robotics, mechatronics, aeronautics, and industrial systems - Contains worked examples which make it ideal for advanced courses as well as for researchers starting to work in the field, particularly suitable for engineers wishing to enter the field quickly and efficiently

Model Identification And Adaptive Control

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Author : Graham Goodwin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Model Identification And Adaptive Control written by Graham Goodwin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.

This book is based on a workshop entitled.: Model " Identification and Adap tive Control: From Windsurfing to Telecommunications" held in Sydney, Aus tralia, on December 16, 2000. The workshop was organized in honour of Pro fessor Brian (BDO) Anderson in recognition of his seminal contributions to systems science over the past 4 decades. . The chapters in the book have been written by colleagues, friends and stu dents of Brian Anderson. A central theme of the book is the inter relationship between identification and the use of models in real world applications. This theme has underpinned much of Brian Anderson's own contributions. The book reflects on these contributions as well as makirig important statements about possible future research directions. The subtitle of the book (From Windsurfing to Telecommunications) rec ognizes the fact that many common life experiences, such as those we en counter when learning to ride a windsurfer are models for design methods that can be used on real world advanced technological control problems. In deed, Brian Anderson extensively explored this link in his research work.

Model Free Adaptive Control

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Author : Zhongsheng Hou
language : en
Publisher: CRC Press
Release Date : 2013-09-24

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.

Data Driven Nonparametric Adaptive Control Theory

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