DocumentCode :
574506
Title :
Decentralized H2 control for multi-channel stochastic systems via state feedback strategies: Application to multimodeling systems
Author :
Mukaidani, Hiroaki ; Tanaka, Hiroya ; Yamamoto, Takayuki
Author_Institution :
Grad. Sch. of Educ., Hiroshima Univ., Higashi-Hiroshima, Japan
fYear :
2012
fDate :
27-29 June 2012
Firstpage :
50
Lastpage :
55
Abstract :
This paper investigates a decentralized H2 state feedback control for multi-channel linear time-invariant stochastic systems governed by Itoô´s differential equation. After establishing the necessary condition based on stochastic algebraic Riccati equation (SARE) for the existence of the strategy set, it is shown that the same conditions can be written by the linear matrix inequality (LMI). The equivalence between the solvability of the SARE and the feasibility of the LMI is proved for the first time by using the Karush-Kuhn-Tucker (KKT) condition. In order to prove the usefulness of the proposed methodology, the extension to the multiparameter singularly perturbed systems (MSPS) is also considered. It is shown that the parameter-independent strategy set can be designed by solving the reduced-order AREs and LMI. Furthermore, as a novel contribution, the degradation of H2 norm for the closed-loop stochastic systems by means of the parameter independent strategy set that is yielded via LMI methods is given. A numerical example is given to demonstrate the useful feature obtained.
Keywords :
H2 control; Riccati equations; closed loop systems; decentralised control; differential equations; linear matrix inequalities; singularly perturbed systems; state feedback; stochastic systems; Ito´s differential equation; Karush-Kuhn-Tucker condition; LMI; MSPS; SARE; closed-loop stochastic systems; decentralized H2 state feedback control; linear matrix inequality; multichannel linear time-invariant stochastic systems; multiparameter singularly perturbed systems; parameter independent strategy set; reduced-order ARE; state feedback strategies; stochastic algebraic Riccati equation; Degradation; Differential equations; Riccati equations; State feedback; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2012
Conference_Location :
Montreal, QC
ISSN :
0743-1619
Print_ISBN :
978-1-4577-1095-7
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2012.6315091
Filename :
6315091
Link To Document :
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