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Title: Variance-constrained dissipative observer-based control for a class of nonlinear stochastic systems with degraded measurements
Authors: Wang, Z
Lam, J
Ma, L
Bo, Y
Guo, Z
Keywords: Nonlinear systems
Stochastic systems
Dissipative control
Variance-constrained control
Degraded measurements
Publication Date: 2011
Publisher: Elsevier
Citation: Journal of Mathematical Analysis and Applications, 377(2): 645-658, May 2011
Abstract: This paper is concerned with the variance-constrained dissipative control problem for a class of stochastic nonlinear systems with multiple degraded measurements, where the degraded probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over a given interval. The purpose of the problem is to design an observer-based controller such that, for all possible degraded measurements, the closed-loop system is exponentially mean-square stable and strictly dissipative, while the individual steady-state variance is not more than the pre-specified upper bound constraints. A general framework is established so that the required exponential mean-square stability, dissipativity as well as the variance constraints can be easily enforced. A sufficient condition is given for the solvability of the addressed multiobjective control problem, and the desired observer and controller gains are characterized in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite programming method. Finally, a numerical example is presented to show the effectiveness and applicability of the proposed algorithm.
Description: The official published version of the article can be obtained from the link below.
Sponsorship: This work was supported in part by the Distinguished Visiting Fellowship of the Royal Academy of Engineering of the UK, the Royal Society of the UK, the GRF HKU 7137/09E, the National Natural Science Foundation of China under Grant 61028008, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, and the Alexander von Humboldt Foundation of Germany.
ISSN: 0022-247X
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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