State estimation for T-S fuzzy affine systems with variable quantization density

Abstract

This paper is concerned with the problem of state estimation for a class of discrete-time Takagi-Sugeno fuzzy affine systems against measurement quantization. The quantization density can be manually adjusted to satisfy different performance requirements at different time instants, which can reduce the amount of transmitted information when the performance requirement for the fuzzy filtering error system is not critical. With the aid of a fuzzy-basis-dependent Lyapunov function and the S-procedure approach, sufficient conditions on the existence of the desired H∞ filters are established to ensure that the fuzzy filtering error system is asymptotically stable with a prescribed H∞ performance index. Finally, a practical example of single-link robot arm is provided to illustrate the effectiveness as well as the smaller transmitted information burden of the proposed state estimation strategy.