Adaptive dynamic programming with applications in optimal control

This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-tim...

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Bibliographic Details
Main Authors Liu, Derong, 1963- (Author), Wei, Qinglai (Author), Wang, Ding (Author), Yang, Xiong (Author), Li, Hongliang (Author)
Format Electronic eBook
LanguageEnglish
Published Cham, Switzerland : Springer, 2017.
SeriesAdvances in industrial control.
Subjects
Dynamic programming.
Control theory.
elektronické knihy
electronic books
Online AccessFull text
ISBN9783319508153
9783319508139
Physical Description1 online resource (xxx, 594 pages)

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Table of Contents:
  • History of Adaptive Dynamic Programming
  • Part I: Continuous-Time Systems
  • Optimal Control of Continuous-Time Affine Nonlinear Systems
  • Optimal Control of Nonaffine Continuous-Time Systems
  • Robust and Guaranteed Cost Control of Continuous-Time Nonlinear Systems
  • Decentralized Stabilization and Control of Nonlinear Interconnected Systems
  • Online Synchronous Optimal Learnign Algorithms for Multiplayer Nonzero-Sum Games with Unknown Dynamics
  • Part II: Discrete-Time Systems
  • Value Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems
  • Finite Approximation Error-Based Value Iteration for Adaptive Dynamic Programming
  • Policy Iteration for Optimal Control of Discrete-Time Nonlinear Systems
  • Generalized Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems
  • Error-Bound Analysis of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems
  • Part III: Applications
  • Adaptive Dynamic Programming for Renewable Energy Scheduling and Battery Management in Smart Homes
  • Adaptive Dynamic Programming for Optimal Tracking Control of a Coal Gasification Process
  • Data-Driven Neuro-Optimal Temperature Control of Water?Gas Shift Reaction.

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