Pareto Optimal Strategy for Stochastic Weakly Coupled Large Scale Systems With State Dependent System Noise

IEEE Transactions on Automatic Control 54 巻 9 号 2244-2250 頁 2009-08-18 発行
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タイトル ( eng )
Pareto Optimal Strategy for Stochastic Weakly Coupled Large Scale Systems With State Dependent System Noise
作成者
Xu Hua
収録物名
IEEE Transactions on Automatic Control
54
9
開始ページ 2244
終了ページ 2250
抄録
This note is concerned with the decentralized infinite horizon stochastic Pareto-optimal static output feedback strategy for a class of weakly coupled systems with state-dependent noise. First, Pareto-optimal control problems are formulated using a static output feedback strategy. The necessary conditions are given by the cross-coupled stochastic algebraic Riccati-type equations (CSAREs) for proving the existence of the static output feedback strategy that minimizes the quadratic cost function. After determining the asymptotic structure of the solutions of the CSAREs, a new sequential numerical algorithm and Newton's method for solving the CSAREs are described. The resulting numerical solution is used to develop the Pareto-optimal strategy. Finally, the efficiency of the proposed algorithm is demonstrated by solving a numerical example for a practical megawatt-frequency control problem.
著者キーワード
Cross-coupled stochastic algebraic Riccati-type equations (CSAREs)
Pareto optimal strategy
static output feedback
stochastic weakly-coupled systems
NDC分類
数学 [ 410 ]
言語
英語
資源タイプ 学術雑誌論文
出版者
IEEE Control Systems Society
発行日 2009-08-18
権利情報
Copyright (c) 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
出版タイプ Version of Record(出版社版。早期公開を含む)
アクセス権 オープンアクセス
収録物識別子
[ISSN] 0018-9286
[DOI] 10.1109/TAC.2009.2026854
[NCID] AA00667671
[DOI] http://dx.doi.org/10.1109/TAC.2009.2026854