TY - GEN
T1 - Output-Dependent Switching Laws for Quadratic Stabilization of Switched Linear Stochastic Systems
AU - Chang, Yufang
AU - Zhai, Guisheng
AU - Xiong, Lianglin
AU - Fu, Bo
N1 - Funding Information:
The authors would like to thank Mr. Ayato Hihara with Shibaura Institute of Technology and Prof. Qiang Yu with Shanxi Normal University for valuable discussion. This research has been supported in part by the National Natural Science Foundation of China (61903129, 11601474) and the Green Industry Leading Program of Hubei University of Technology (CPYF2017003), and in part by the Japan Ministry of Education, Sciences and Culture under Grants-in-Aid for Scientific Research (C) 21560471.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - We consider global quadratic stabilization in probability for switched linear stochastic systems (SLSS). Assuming that no single subsystem is globally quadratically stable in probability (GQS-P), we propose both static and dynamic output-dependent switching laws such that the entire switched system is GQS-P. In the case of static output-dependent switching, the sufficient condition is expressed by a set of matrix inequalities, while the design of dynamic output-dependent switching is based on a convex combination of subsystems and a robust Luenberger observer for each subsystem. A numerical example is provided to show effectiveness of the proposed approach.
AB - We consider global quadratic stabilization in probability for switched linear stochastic systems (SLSS). Assuming that no single subsystem is globally quadratically stable in probability (GQS-P), we propose both static and dynamic output-dependent switching laws such that the entire switched system is GQS-P. In the case of static output-dependent switching, the sufficient condition is expressed by a set of matrix inequalities, while the design of dynamic output-dependent switching is based on a convex combination of subsystems and a robust Luenberger observer for each subsystem. A numerical example is provided to show effectiveness of the proposed approach.
KW - Switched linear stochastic systems (SLSS)
KW - convex combination
KW - globally quadratically stable in probability (GQS-P)
KW - linear matrix inequalities (LMIs)
KW - output-dependent switching
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U2 - 10.1109/CCDC49329.2020.9164650
DO - 10.1109/CCDC49329.2020.9164650
M3 - Conference contribution
AN - SCOPUS:85091594423
T3 - Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
SP - 1796
EP - 1801
BT - Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd Chinese Control and Decision Conference, CCDC 2020
Y2 - 22 August 2020 through 24 August 2020
ER -