Approximate dynamic programming for output feedback control

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

Abstract

This paper studies the adaptive and optimal output feedback control problem using approximate dynamic programming. It is shown that, under the recursive algorithm, the control policy converges to its optimal value, up to a constant proportional to the magnitude of the inaccuracy caused by observation errors. On the basis of this result, direct adaptive output feedback strategies are developed for solving both discrete-time and continuous-time LQR problems with uncertain parameters. Finally, numerical examples are given to demonstrate the efficiency of the proposed control schemes.

Original languageEnglish (US)
Title of host publicationProceedings of the 29th Chinese Control Conference, CCC'10
Pages5815-5820
Number of pages6
StatePublished - 2010
Event29th Chinese Control Conference, CCC'10 - Beijing, China
Duration: Jul 29 2010Jul 31 2010

Publication series

NameProceedings of the 29th Chinese Control Conference, CCC'10

Other

Other29th Chinese Control Conference, CCC'10
CountryChina
CityBeijing
Period7/29/107/31/10

Keywords

  • ADP
  • Adaptive control
  • Policy iteration
  • Reinforcement learning

ASJC Scopus subject areas

  • Control and Systems Engineering

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