DocumentCode
630607
Title
Infinite-horizon linear quadratic optimal control for discrete-time LTI systems with random input gains
Author
Jianying Zheng ; Li Qiu
Author_Institution
Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear
2013
fDate
17-19 June 2013
Firstpage
1195
Lastpage
1200
Abstract
In this paper we continue our study of the infinite-horizon linear quadratic (LQ) optimal control for linear time-invariant (LTI) discrete systems with random input gains. In our previous work, it is shown that the LQ optimal control problem with an internal stability requirement is solvable if and only if a mean-square stabilizing solution to the associated modified algebraic Riccati equation (MARE) exists. Moreover, the optimal controller is a linear state feedback. In this paper, we focus on investigating the conditions ensuring the existence of a mean-square stabilizing solution to the MARE. The observability and detectability as well as stabilizability for stochastic systems are defined in the mean-square sense which play essential roles in the LQ optimal control. By channel/controller co-design, we obtain a sufficient condition ensuring the existence of the mean-square stabilizing solution to the MARE.
Keywords
Riccati equations; control system synthesis; discrete time systems; infinite horizon; linear quadratic control; mean square error methods; observability; stability; state feedback; stochastic systems; LQ optimal control problem; MARE; channel-controller co-design; detectability; discrete-time LTI systems; infinite-horizon linear quadratic optimal control; linear state feedback; linear time-invariant discrete systems; mean-square stabilizing solution; modified algebraic Riccati equation; observability; random input gains; stabilizability; stochastic systems; Channel capacity; Closed loop systems; Observability; Optimal control; Resource management; State feedback; Stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2013
Conference_Location
Washington, DC
ISSN
0743-1619
Print_ISBN
978-1-4799-0177-7
Type
conf
DOI
10.1109/ACC.2013.6579998
Filename
6579998
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