Learning Based Adaptive Control
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Learning Based Adaptive Control
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Author : Mouhacine Benosman
language : en
Publisher: Butterworth-Heinemann
Release Date : 2016-08-02
Learning Based Adaptive Control written by Mouhacine Benosman and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-02 with Technology & Engineering categories.
Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. - Includes a good number of Mechatronics Examples of the techniques. - Compares and blends Model-free and Model-based learning algorithms. - Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.
Learning For Adaptive And Reactive Robot Control
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Author : Aude Billard
language : en
Publisher: MIT Press
Release Date : 2022-02-08
Learning For Adaptive And Reactive Robot Control written by Aude Billard and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-08 with Technology & Engineering categories.
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Applications Of Neural Adaptive Control Technology
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Author : Jens Kalkkuhl
language : en
Publisher: World Scientific
Release Date : 1997
Applications Of Neural Adaptive Control Technology written by Jens Kalkkuhl and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Technology & Engineering categories.
This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.
Adaptive Control Tutorial
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Author : Petros Ioannou
language : en
Publisher: SIAM
Release Date : 2006-01-01
Adaptive Control Tutorial written by Petros Ioannou and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Mathematics categories.
Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index
Optimal Adaptive Control And Differential Games By Reinforcement Learning Principles
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Author : Draguna L. Vrabie
language : en
Publisher: IET
Release Date : 2013
Optimal Adaptive Control And Differential Games By Reinforcement Learning Principles written by Draguna L. Vrabie and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
The book reviews developments in the following fields: optimal adaptive control; online differential games; reinforcement learning principles; and dynamic feedback control systems.
Nonlinear And Adaptive Control With Applications
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Author : Alessandro Astolfi
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-06
Nonlinear And Adaptive Control With Applications written by Alessandro Astolfi 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 2007-12-06 with Technology & Engineering categories.
The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.
Adaptive And Learning Based Control Of Safety Critical Systems
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Author : Max Cohen
language : en
Publisher: Springer Nature
Release Date : 2023-06-16
Adaptive And Learning Based Control Of Safety Critical Systems written by Max Cohen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with Technology & Engineering categories.
This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors provide a self-contained treatment of learning-based control techniques with rigorous guarantees of stability and safety. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas. The authors bring together control theory, optimization, machine learning, and formal methods and present worked-out examples and extensive simulation examples to complement the mathematical style of presentation. Prerequisites are minimal, and the underlying ideas are accessible to readers with only a brief background in control-theoretic ideas, such as Lyapunov stability theory.
Neural Network Based Adaptive Control Of Uncertain Nonlinear Systems
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Author : Kasra Esfandiari
language : en
Publisher: Springer Nature
Release Date : 2021-06-18
Neural Network Based Adaptive Control Of Uncertain Nonlinear Systems written by Kasra Esfandiari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Technology & Engineering categories.
The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.
Robust Adaptive Control
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Author : Petros A. Ioannou
language : en
Publisher: Courier Corporation
Release Date : 2012-12-19
Robust Adaptive Control written by Petros A. Ioannou and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-19 with Technology & Engineering categories.
" Presented in a tutorial style, this text reduces the confusion and difficulty in grasping the design, analysis, and robustness of a wide class of adaptive controls for continuous-time plants. The treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Excellent text and authoritative reference"--
Evolutionary Learning Algorithms For Neural Adaptive Control
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Author : Dimitris C. Dracopoulos
language : en
Publisher: Springer
Release Date : 2013-12-21
Evolutionary Learning Algorithms For Neural Adaptive Control written by Dimitris C. Dracopoulos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-21 with Computers categories.
Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.