Optimal control for a class of nonlinear systems with state delay based on Adaptive Dynamic Programming with ε-error bound

Xiaofeng Lin, Nuyun Cao, Yuzhang Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a finite-horizon ε-optimal control for a class of nonlinear systems with state delay is proposed by Adaptive Dynamic Programming (ADP) algorithm. First of all, the performance index function is defined and the Hamilton-Jacobi-Bellman (HJB) equation is obtained for the problem, the convergence of the iterative algorithm is also presented. Then, ADP algorithm for finite-horizon optimal control is introduced with an ε-error bound so as to get the ε-optimal control, and BP neural network is used to implement ADP algorithm. At last, an example is given to demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Pages177-182
Number of pages6
DOIs
StatePublished - 2013
Event2013 4th IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL 2013 - Singapore, Singapore
Duration: Apr 16 2013Apr 19 2013

Publication series

NameIEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL
ISSN (Print)2325-1824
ISSN (Electronic)2325-1867

Conference

Conference2013 4th IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL 2013
Country/TerritorySingapore
CitySingapore
Period4/16/134/19/13

Keywords

  • ε-optimal control
  • Adaptive Dynamic Programming
  • finite time
  • nonlinear systems
  • state delay

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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