Abstract

In this paper, the Singular-Polynomial-Fuzzy-Model (SPFM) approach problem and impulse elimination are investigated based on sliding mode control for a class of nonlinear singular system (NSS) with impulses. Considering two numerical examples, the SPFM of the nonlinear singular system is calculated based on the compound function type and simple function type. According to the solvability and the steps of two numerical examples, the method of solving the SPFM form of the nonlinear singular system with (and without) impulse are extended to the more general case. By using the Heine–Borel finite covering theorem, it is proven that a class of nonlinear singular systems with bounded impulse-free item (BIFI) properties and separable impulse item (SII) properties can be approximated by SPFM with arbitrary accuracy. The linear switching function and sliding mode control law are designed to be applied to the impulse elimination of SPFM. Compared with some published works, a human posture inverted pendulum model example and Example 3.2 demonstrate that the approximation error is small enough and that both algorithms are effective. Example 3.3 is to illustrate that sliding mode control can effectively eliminate impulses of SPFM.

Highlights

  • The Takagi–Sugeno (T-S) fuzzy model was put forward by T

  • It is proven that a class of nonlinear singular system with a bounded impulse-free item property and a separable impulse item property can be approximated by SPFM with arbitrary accuracy

  • The linear switching function and sliding mode control law are designed to be applied to the impulse elimination of the SPFM

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Summary

Introduction

The Takagi–Sugeno (T-S) fuzzy model was put forward by T. In 1985, and they proposed a new type of fuzzy model representation. Many scholars [3,4,5,6,7] have proven that the above conclusions can be adapted to various fuzzy systems. In [8], the finite-time stabilization of a class of stochastic nonlinear systems was studied by applying the fuzzy-logic systems to approximate the unknown nonlinearities and a novel adaptive finite-time control strategy was proposed. A new fuzzy model has been proposed by K. Tanaka [10], that is, a polynomial fuzzy model. In essence, it is a more extensive form of the T-S fuzzy model. The number of fuzzy rules in the polynomial fuzzy model is much less than that in the T-S fuzzy model when describing the same nonlinear systems

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