期刊
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
卷 23, 期 7, 页码 815-826出版社
WILEY
DOI: 10.1002/rnc.2788
关键词
gain-scheduled control; randomly occurring nonlinearities; time-varying Bernoulli distribution; probability-dependent Lyapunov function; sector-nonlinearity; parameter-varying systems; discrete-time stochastic systems
资金
- Leverhulme Trust of the UK
- Engineering and Physical Sciences Research Council (EPSRC) of the UK [GR/S27658/01]
- National Natural Science Foundation of China [61028008, 61134009, 61074016, 61104125, 60974030]
- Shanghai Natural Science Foundation of China [10ZR1421200]
- Alexander von Humboldt Foundation of Germany
In this paper, the gain-scheduled control problem is addressed by using probability-dependent Lyapunov functions for a class of discrete-time stochastic delayed systems with randomly occurring sector nonlinearities. The sector nonlinearities are assumed to occur according to a time-varying Bernoulli distribution with measurable probability in real time. The multiplicative noises are given by means of a scalar Gaussian white noise sequence with known variances. The aim of the addressed gain-scheduled control problem is to design a controller with scheduled gains such that, for the admissible randomly occurring nonlinearities, time delays and external noise disturbances, the closed-loop system is exponentially mean-square stable. Note that the designed gain-scheduled controller is based on the measured time-varying probability and is therefore less conservative than the conventional controller with constant gains. It is shown that the time-varying controller gains can be derived in terms of the measurable probability by solving a convex optimization problem via the semi-definite programme method. A simulation example is exploited to illustrate the effectiveness of the proposed design procedures. Copyright (c) 2012 John Wiley & Sons, Ltd.
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