Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming

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

Research output: Contribution to journalArticle

Abstract

This paper studies the adaptive and optimal output-feedback problem for continuous-time uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback control policies are developed by approximate/adaptive dynamic programming (ADP) based on both policy iteration and value iteration methods. The obtained adaptive and optimal output-feedback controllers differ from the existing literature on the ADP in that they are derived from sampled-data systems theory and are guaranteed to be robust to dynamic uncertainties. A small-gain condition is given under which the overall system is globally asymptotically stable at the origin. An application to power systems is given to test the effectiveness of the proposed approaches.

Original languageEnglish (US)
Pages (from-to)37-45
Number of pages9
JournalAutomatica
Volume72
DOIs
StatePublished - Oct 1 2016

Keywords

  • Approximate/adaptive dynamic programming (ADP)
  • Nonlinear dynamic uncertainty
  • Output-feedback control
  • Robust optimal control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming'. Together they form a unique fingerprint.

  • Cite this