Global Quadratic Stabilization in Probability for Switched Linear Stochastic Systems

Global quadratic stabilization in probability is considered for both switched linear certain stochastic systems and switched linear uncertain stochastic systems where there are norm bounded uncertainties. Under the assumption that every single subsystem is NOT globally quadratically stable in probab...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.103610-103618
Main Authors: Chang, Yufang, Zhai, Guisheng, Xiong, Lianglin, Fu, Bo
Format: Article
Language:English
Subjects:
Algorithms
convex combination
globally quadratically stable in probability (GQS-P)
Linear matrix inequalities
LMIs
norm bounded uncertainties
output based switching
Probability theory
Robustness (mathematics)
Stabilization
Stochastic systems
Subsystems
Switched linear certain stochastic systems (SLCSS)
switched linear uncertain stochastic systems (SLUSS)
Switched systems
Switches
Switching
Symmetric matrices
Uncertainty
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Summary:Global quadratic stabilization in probability is considered for both switched linear certain stochastic systems and switched linear uncertain stochastic systems where there are norm bounded uncertainties. Under the assumption that every single subsystem is NOT globally quadratically stable in probability (GQS-P), we propose both static and dynamic output based switching laws such that the switched system on hand is GQS-P. In the case of static output based switching, the condition is expressed by a set of matrix inequalities, while the design of dynamic output based switching is proposed with a convex combination of subsystems and a robust Luenberger observer for each subsystem. Numerical examples are presented to show validity of the design conditions and switching algorithms.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2999159