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

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

doi:10.1016/j.automatica.2016.05.008

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

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

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Pages (from-to)	37-45
Number of pages	9
Journal	Automatica
Volume	72
DOIs	https://doi.org/10.1016/j.automatica.2016.05.008
State	Published - 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

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10.1016/j.automatica.2016.05.008

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title = "Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming",

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.",

keywords = "Approximate/adaptive dynamic programming (ADP), Nonlinear dynamic uncertainty, Output-feedback control, Robust optimal control",

author = "Weinan Gao and Yu Jiang and Jiang, {Zhong Ping} and Tianyou Chai",

note = "Publisher Copyright: {\textcopyright} 2016 Elsevier Ltd",

year = "2016",

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doi = "10.1016/j.automatica.2016.05.008",

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AU - Gao, Weinan

AU - Jiang, Yu

AU - Jiang, Zhong Ping

AU - Chai, Tianyou

PY - 2016/10/1

Y1 - 2016/10/1

N2 - 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.

AB - 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.

KW - Approximate/adaptive dynamic programming (ADP)

KW - Nonlinear dynamic uncertainty

KW - Output-feedback control

KW - Robust optimal control

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SP - 37

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JO - Automatica

JF - Automatica

ER -

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

Abstract

Keywords

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