Decentralized Adaptive Optimal Control of Large-Scale Systems with Application to Power Systems

Tao Bian; Yu Jiang; Zhong Ping Jiang

doi:10.1109/TIE.2014.2345343

Decentralized Adaptive Optimal Control of Large-Scale Systems with Application to Power Systems

Tao Bian, Yu Jiang, Zhong Ping Jiang

Electrical and Computer Engineering

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

Abstract

This paper studies the optimal control problem for large-scale systems with unknown parameters and dynamics. By using robust adaptive dynamic programming (RADP) method, a decentralized optimal control design is given for large-scale systems with unmatched uncertainties. The convergence of the proposed RADP algorithm and the asymptotic stability of the closed-loop large-scale system are studied rigorously. Finally, a numerical example of a large-scale power system is adopted to illustrate the effectiveness of the obtained algorithm.

Original language	English (US)
Article number	7055987
Pages (from-to)	2439-2447
Number of pages	9
Journal	IEEE Transactions on Industrial Electronics
Volume	62
Issue number	4
DOIs	https://doi.org/10.1109/TIE.2014.2345343
State	Published - Apr 2015

Keywords

Adaptive dynamic programming (ADP)
adaptive optimal control
power systems

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/TIE.2014.2345343

Cite this

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title = "Decentralized Adaptive Optimal Control of Large-Scale Systems with Application to Power Systems",

abstract = "This paper studies the optimal control problem for large-scale systems with unknown parameters and dynamics. By using robust adaptive dynamic programming (RADP) method, a decentralized optimal control design is given for large-scale systems with unmatched uncertainties. The convergence of the proposed RADP algorithm and the asymptotic stability of the closed-loop large-scale system are studied rigorously. Finally, a numerical example of a large-scale power system is adopted to illustrate the effectiveness of the obtained algorithm.",

keywords = "Adaptive dynamic programming (ADP), adaptive optimal control, power systems",

author = "Tao Bian and Yu Jiang and Jiang, {Zhong Ping}",

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N2 - This paper studies the optimal control problem for large-scale systems with unknown parameters and dynamics. By using robust adaptive dynamic programming (RADP) method, a decentralized optimal control design is given for large-scale systems with unmatched uncertainties. The convergence of the proposed RADP algorithm and the asymptotic stability of the closed-loop large-scale system are studied rigorously. Finally, a numerical example of a large-scale power system is adopted to illustrate the effectiveness of the obtained algorithm.

AB - This paper studies the optimal control problem for large-scale systems with unknown parameters and dynamics. By using robust adaptive dynamic programming (RADP) method, a decentralized optimal control design is given for large-scale systems with unmatched uncertainties. The convergence of the proposed RADP algorithm and the asymptotic stability of the closed-loop large-scale system are studied rigorously. Finally, a numerical example of a large-scale power system is adopted to illustrate the effectiveness of the obtained algorithm.

KW - Adaptive dynamic programming (ADP)

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Decentralized Adaptive Optimal Control of Large-Scale Systems with Application to Power Systems

Abstract

Keywords

ASJC Scopus subject areas

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