Adaptive Dynamic Programming and Adaptive Optimal Output Regulation of Linear Systems

Weinan Gao, Zhong Ping Jiang

Research output: Contribution to journalArticlepeer-review


This note studies the adaptive optimal output regulation problem for continuous-time linear systems, which aims to achieve asymptotic tracking and disturbance rejection by minimizing some predefined costs. Reinforcement learning and adaptive dynamic programming techniques are employed to compute an approximated optimal controller using input/partial-state data despite unknown system dynamics and unmeasurable disturbance. Rigorous stability analysis shows that the proposed controller exponentially stabilizes the closed-loop system and the output of the plant asymptotically tracks the given reference signal. Simulation results on a LCL coupled inverter-based distributed generation system demonstrate the effectiveness of the proposed approach.

Original languageEnglish (US)
Article number7444144
Pages (from-to)4164-4169
Number of pages6
JournalIEEE Transactions on Automatic Control
Issue number12
StatePublished - Dec 2016


  • Adaptive control
  • approximate/adaptive dynamic programming (ADP)
  • optimal control
  • output regulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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