State estimation for time-delay systems with probabilistic sensor gain reductions

This paper presents a new state estimation problem for a class of time-delay systems with probabilistic sensor gain faults. The sensor gain reductions are described by a stochastic variable that obeys the uniform distribution in a known interval [alpha, beta], which is a natural reflection of the probabilistic performance deterioration of sensors when gain reduction faults occur. Attention is focused on the design of a state estimator such that for all possible sensor faults and all external disturbances, the filtering error dynamic is asymptotically mean-square stable as well as fulfils a prescribed disturbance attenuation level. The existence of desired filters is proved to depend on the feasibility of a certain linear matrix inequality (LMI), and a numerical example is given to illustrate the effectiveness of the proposed design approach. (c) 2008 Curtin University of Technology and John Wiley & Sons, Ltd.