Adaptive and optimal output feedback control of linear systems: An adaptive dynamic programming approach

Weinan Gao, Yu Jiang, Zhong Ping Jiang, Tianyou Chai

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

Abstract

This paper proposes a computational adaptive optimal output feedback control method for continuous-time linear systems. By periodic sampling, we use measurable input/output data to reconstruct the unmeasurable state, and then utilize adaptive dynamic programming (ADP) technique to iteratively solve the discrete-time algebraic Riccati equation. An exploration noise is introduced for online learning purpose without compromising accuracy of the proposed iterative algorithm. The stability and the optimality of the sampled-data system in close-loop with the proposed control policy are also analyzed. The feasibility of the output feedback ADP scheme is validated by simulation on a third-order linear system.

Original languageEnglish (US)
Title of host publicationProceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2085-2090
Number of pages6
EditionMarch
ISBN (Electronic)9781479958252
DOIs
StatePublished - Mar 2 2015
Event2014 11th World Congress on Intelligent Control and Automation, WCICA 2014 - Shenyang, China
Duration: Jun 29 2014Jul 4 2014

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)
NumberMarch
Volume2015-March

Other

Other2014 11th World Congress on Intelligent Control and Automation, WCICA 2014
Country/TerritoryChina
CityShenyang
Period6/29/147/4/14

Keywords

  • Approximate/adaptive dynamic programming(ADP)
  • Optimal control
  • Output feedback
  • Sampled-data systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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