Multiplicative Fault Estimation‐Based Adaptive Sliding Mode Fault‐Tolerant Control Design for Nonlinear Systems

Abstract

This article deals with the sliding mode fault‐tolerant control (FTC) problem for a nonlinear system described under Takagi‐Sugeno (T‐S) fuzzy representation. In particular, the nonlinear system is corrupted with multiplicative actuator faults, process faults, and uncertainties. We start by constructing the separated FTC design to ensure robust stability of the closed‐loop nonlinear system. First, we propose to conceive an adaptive observer in order to estimate nonlinear system states, as well as robust multiplicative fault estimation. The novelty of the proposed approach is that the observer gains are obtained by solving the multiobjective linear matrix inequality (LMI) optimization problem. Second, an adaptive sliding mode controller is suggested to offer a solution to stabilize the closed‐loop system despite the occurrence of real fault effects. Compared with the separated FTC, this paper provides an integrated sliding mode FTC in order to achieve an optimal robustness interaction between observer and controller models. Thus, in a single‐step LMI formulation, sufficient conditions are developed with multiobjective optimization performances to guarantee the stability of the closed‐loop system. At last, nonlinear simulation results are given to illustrate the effectiveness of the proposed FTC to treat multiplicative faults.