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Abstract and Applied Analysis
Volume 2013, Article ID 629621, 10 pages
Research Article

Nonfragile Gain-Scheduled Control for Discrete-Time Stochastic Systems with Randomly Occurring Sensor Saturations

1Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2Department of Engineering, Faculty of Engineering and Science, University of Agder, N-4898 Grimstad, Norway
3School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China

Received 10 May 2013; Accepted 22 June 2013

Academic Editor: Jun Hu

Copyright © 2013 Wangyan Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper is devoted to tackling the control problem for a class of discrete-time stochastic systems with randomly occurring sensor saturations. The considered sensor saturation phenomenon is assumed to occur in a random way based on the time-varying Bernoulli distribution with measurable probability in real time. The aim of the paper is to design a nonfragile gain-scheduled controller with probability-dependent gains which can be achieved by solving a convex optimization problem via semidefinite programming method. Subsequently, a new kind of probability-dependent Lyapunov functional is proposed in order to derive the controller with less conservatism. Finally, an illustrative example will demonstrate the effectiveness of our designed procedures.