Lower Triangle Factor-Based Fault Estimation and Fault Tolerant Control for Fuzzy Systems

摘要

This article focuses on the problems of observer-based fault estimation and dynamic output feedback fault tolerant control (FTC) for a class of nonlinear fuzzy systems with faults. A novel lower triangle factor-based estimation observer (LTFEO) is proposed for the first time. The designed LTFEO can reduce to the traditional robust estimation observer (REO) and is superior to the adaptive estimation observer (AEO) in the relevant literature, furthermore, the designed LTFEO does not contain the output derivatives. The initial estimation accuracy is improved under the designed estimation observer. An iterative estimation algorithm based on the iterative LTFEOs is given, by which, the obtained mean sequence of state and fault estimation errors can converge to zeros (vector) and the proof is given in theoretical. Then, a new dynamic output feedback FTC is designed to stabilize the faulty system, where the output feedback gains can be determined by state feedback gains and the computational difficulty is decreased. Less conservative stability conditions for the estimation error dynamics and the closed-loop system are given in terms of linear matrix inequalities (LMIs). A tunnel diode circuit system is applied to test the effectiveness and merits of the proposed methods.