DocumentCode :
623414
Title :
Gain scheduled H-infinity control for nonlinear stochastic systems with mixed uncertainties
Author :
Yanqing Liu ; Yanyan Yin ; Fei Liu ; Peng Shi ; Kok Lay Teo
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
fYear :
2013
fDate :
19-21 June 2013
Firstpage :
1544
Lastpage :
1549
Abstract :
This paper studies the problem of robust gain-scheduled H controller design for a class of nonlinear Markov jump systems with mixed uncertainties, one is time-varying transition probabilities, which follows a nonhomogeneous jump process, and the other one is parameter uncertainty. Nonlinearity of such systems is linearized by means of gradient linearization procedure, and stochastic linear models are constructed in the vicinity of selected operating states, the time varying transition probability matrix is described as a polytope set. By Lyapunov function approach, under the designed controller, a sufficient condition is presented to ensure the resulting closed-loop system is stochastically stable and a prescribed H performance index is satisfied. Finally, continuous gain-scheduled approach is employed to design continuous time-varying controller on the entire nonlinear jump system. A simulation example is given to illustrate the effectiveness of developed techniques.
Keywords :
H control; Lyapunov methods; closed loop systems; continuous time systems; control nonlinearities; control system synthesis; gradient methods; linearisation techniques; matrix algebra; nonlinear control systems; probability; robust control; stochastic systems; uncertain systems; H performance index; Lyapunov function approach; closed-loop system; continuous gain-scheduled approach; continuous time-varying controller design; gain scheduled H-infinity control; gradient linearization procedure; mixed uncertainties; nonhomogeneous jump process; nonlinear Markov jump systems; nonlinear stochastic systems; parameter uncertainty; polytope set; robust gain-scheduled H controller design; stochastic linear models; stochastic stability; system nonlinearity; time varying transition probability matrix; Educational institutions; Markov processes; Robustness; Symmetric matrices; Time-varying systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-6320-4
Type :
conf
DOI :
10.1109/ICIEA.2013.6566613
Filename :
6566613
Link To Document :
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