Event-Triggered Mixed Non-Fragile and Measurement Quantization Filtering Design for Interval Type-2 Fuzzy Systems

Chunsong Han,Jiafeng Yu,Guangtao Ran,Dingding Song

doi:10.1109/access.2020.3046748

Abstract

This paper is concerned with the problem of event-triggered non-fragile $H_{\infty }$ filter design for interval type-2 (IT2) fuzzy systems subject to output quantization. The nonlinear plant is efficiently described by an IT2 fuzzy model, and the lower and upper membership functions with weighting coefficients are employed to characterize parameter uncertainties in the plant. To enhance filter adaptability, an IT2 non-fragile fuzzy filter method is proposed to acquire available information for the unknown state of the plant, where the multiplicative gain variations is taken into account in the filter analysis design process. In order to avoid continuous communications and save limited bandwidth, a dynamic event-based mechanism is employed to adopt the limited communications links. Then, based on the Lyapunov theory together with the inequality technique, a filtering system with event-based mechanism and measurement quantization is analyzed and constructed. Moreover, the obtained sufficient conditions for system analysis are given in the form of linear matrix inequalities (LMIs). Finally, a numerical simulation is provided to verify the effectiveness of the proposed filter design strategy.

Highlights

In the field of theoretical research and engineering applications, Takagi-Sugeno(T-S) fuzzy model is proposed to deal with system nonlinearities, which was first established in [1], [2]
It describes the nonlinear systems by average weighted summation of some local linear sub-models. By using of this replaceable model of nonlinear systems, the controller can be designed by utilizing the parallel distributed compensation scheme. This structure gives a general alternative method for the analysis and synthesis of nonlinear systems, which is called as the type-1 T-S fuzzy model
Fruitful issues were reported for type-1 fuzzy systems

Summary

Introduction

In the field of theoretical research and engineering applications, Takagi-Sugeno(T-S) fuzzy model is proposed to deal with system nonlinearities, which was first established in [1], [2]. It describes the nonlinear systems by average weighted summation of some local linear sub-models. By using of this replaceable model of nonlinear systems, the controller can be designed by utilizing the parallel distributed compensation scheme.

Objectives

Results

Conclusion