DocumentCode :
620560
Title :
Probability-dependent gain-scheduled control for discrete-time stochastic systems with randomly occurring sensor saturations
Author :
Wangyan Li ; Guoliang Wei ; Fei Han
Author_Institution :
Dept. of Control Sci. & Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
fYear :
2013
fDate :
25-27 May 2013
Firstpage :
4728
Lastpage :
4733
Abstract :
This paper is devoted to tackling the control problem for a class of discrete-time stochastic systems with randomly occurring sensor saturations by utilizing gain-scheduled method, the sensor saturation phenomenon is assumed to occur in a randomly way based on time-varying Bernoulli distribution with measurable probability in real time. The aim of the paper is to design a gain-scheduled controller with probability-dependent gain which can be achieved by solving a convex optimization problem via semi-definite programme method. Subsequently, a new kind functional, probability-dependent Lyapunov functional is proposed to make the theory sound. Finally, an illustration example will demonstrate the effectiveness of the procedures we design.
Keywords :
Lyapunov methods; control system synthesis; convex programming; discrete time systems; gain control; probability; sensors; stochastic systems; Lyapunov functional; convex optimization; discrete-time stochastic systems; gain-scheduled controller design; probability-dependent gain; randomly occurring sensor saturations; real time; semidefinite programme method; time-varying Bernoulli distribution; Closed loop systems; Delays; Gain measurement; Stochastic systems; Symmetric matrices; Time-varying systems; Gain-Scheduled Controller; Probability-Dependent Lyapunov Functional; Randomly Occurring Sensor Saturations; Time-Varying Bernoulli Distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
Type :
conf
DOI :
10.1109/CCDC.2013.6561789
Filename :
6561789
Link To Document :
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