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Self-Learning Optimal Control of Nonlinear Systems

Adaptive Dynamic Programming Approach

  • Qinglai Wei
  • Ruizhuo Song
  • Benkai Li
  • Xiaofeng Lin

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 103)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages 1-17
  3. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages 47-84
  4. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages 85-109
  5. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages 111-131
  6. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages 201-214
  7. Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
    Pages E1-E1
  8. Back Matter
    Pages 229-230

About this book

Introduction

This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.

With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.

Keywords

Intelligence Control Adaptive Dynamic Programming Self-Learning Control Nonlinear Systems Neural Network-Based Control

Authors and affiliations

  • Qinglai Wei
    • 1
  • Ruizhuo Song
    • 2
  • Benkai Li
    • 3
  • Xiaofeng Lin
    • 4
  1. 1.Institute of AutomationChinese Academy of SciencesBeijingChina
  2. 2.University of Science and Technology BeijingBeijingChina
  3. 3.Institute of AutomationChinese Academy of SciencesBeijingChina
  4. 4.Guangxi UniversityGuangxiChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-4080-1
  • Copyright Information Science Press, Beijing and Springer Nature Singapore Pte Ltd. 2018
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-10-4079-5
  • Online ISBN 978-981-10-4080-1
  • Series Print ISSN 2198-4182
  • Series Online ISSN 2198-4190
  • Buy this book on publisher's site
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