Adaptive Optimal Control

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Adaptive Optimal Control

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Author : Robert R. Bitmead
language : en
Publisher:
Release Date : 1990

Adaptive Optimal Control written by Robert R. Bitmead and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.

Exploring connections between adaptive control theory and practice, this book treats the techniques of linear quadratic optimal control and estimation (Kalman filtering), recursive identification, linear systems theory and robust arguments.

Adaptive Dynamic Programming Single And Multiple Controllers

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Author : Ruizhuo Song
language : en
Publisher: Springer
Release Date : 2018-12-28

Adaptive Dynamic Programming Single And Multiple Controllers written by Ruizhuo Song and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-28 with Technology & Engineering categories.

This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.

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.

Optimal Control

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Author : Frank L. Lewis
language : en
Publisher: John Wiley & Sons
Release Date : 2012-02-01

Optimal Control written by Frank L. Lewis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-01 with Technology & Engineering categories.

A NEW EDITION OF THE CLASSIC TEXT ON OPTIMAL CONTROL THEORY As a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes that have occurred in recent years. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include: Static Optimization Optimal Control of Discrete-Time Systems Optimal Control of Continuous-Time Systems The Tracking Problem and Other LQR Extensions Final-Time-Free and Constrained Input Control Dynamic Programming Optimal Control for Polynomial Systems Output Feedback and Structured Control Robustness and Multivariable Frequency-Domain Techniques Differential Games Reinforcement Learning and Optimal Adaptive Control

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

Adaptive Optimal Control

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Author : Robert R. Bitmead
language : en
Publisher:
Release Date : 1990

Adaptive Optimal Control written by Robert R. Bitmead and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Uyarlanabilir Denetim Sistemi categories.

Optimal Predictive And Adaptive Control

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Author : Edoardo Mosca
language : en
Publisher: Pearson Education
Release Date : 1995

Optimal Predictive And Adaptive Control written by Edoardo Mosca and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Mathematics categories.

Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.

Reinforcement Learning And Optimal Control

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Author : Dimitri Bertsekas
language : en
Publisher: Athena Scientific
Release Date : 2019-07-01

Reinforcement Learning And Optimal Control written by Dimitri Bertsekas and has been published by Athena Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-01 with Computers categories.

This book considers large and challenging multistage decision problems, which can be solved in principle by dynamic programming (DP), but their exact solution is computationally intractable. We discuss solution methods that rely on approximations to produce suboptimal policies with adequate performance. These methods are collectively known by several essentially equivalent names: reinforcement learning, approximate dynamic programming, neuro-dynamic programming. They have been at the forefront of research for the last 25 years, and they underlie, among others, the recent impressive successes of self-learning in the context of games such as chess and Go. Our subject has benefited greatly from the interplay of ideas from optimal control and from artificial intelligence, as it relates to reinforcement learning and simulation-based neural network methods. One of the aims of the book is to explore the common boundary between these two fields and to form a bridge that is accessible by workers with background in either field. Another aim is to organize coherently the broad mosaic of methods that have proved successful in practice while having a solid theoretical and/or logical foundation. This may help researchers and practitioners to find their way through the maze of competing ideas that constitute the current state of the art. This book relates to several of our other books: Neuro-Dynamic Programming (Athena Scientific, 1996), Dynamic Programming and Optimal Control (4th edition, Athena Scientific, 2017), Abstract Dynamic Programming (2nd edition, Athena Scientific, 2018), and Nonlinear Programming (Athena Scientific, 2016). However, the mathematical style of this book is somewhat different. While we provide a rigorous, albeit short, mathematical account of the theory of finite and infinite horizon dynamic programming, and some fundamental approximation methods, we rely more on intuitive explanations and less on proof-based insights. Moreover, our mathematical requirements are quite modest: calculus, a minimal use of matrix-vector algebra, and elementary probability (mathematically complicated arguments involving laws of large numbers and stochastic convergence are bypassed in favor of intuitive explanations). The book illustrates the methodology with many examples and illustrations, and uses a gradual expository approach, which proceeds along four directions: (a) From exact DP to approximate DP: We first discuss exact DP algorithms, explain why they may be difficult to implement, and then use them as the basis for approximations. (b) From finite horizon to infinite horizon problems: We first discuss finite horizon exact and approximate DP methodologies, which are intuitive and mathematically simple, and then progress to infinite horizon problems. (c) From deterministic to stochastic models: We often discuss separately deterministic and stochastic problems, since deterministic problems are simpler and offer special advantages for some of our methods. (d) From model-based to model-free implementations: We first discuss model-based implementations, and then we identify schemes that can be appropriately modified to work with a simulator. The book is related and supplemented by the companion research monograph Rollout, Policy Iteration, and Distributed Reinforcement Learning (Athena Scientific, 2020), which focuses more closely on several topics related to rollout, approximate policy iteration, multiagent problems, discrete and Bayesian optimization, and distributed computation, which are either discussed in less detail or not covered at all in the present book. The author's website contains class notes, and a series of videolectures and slides from a 2021 course at ASU, which address a selection of topics from both books.

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"--