Fuzzy control design of uncertain nonlinear active fault tolerant control systems

By considering the random nature of the failure events and the FDI (failure detection and isolation) decisions in real FTC (fault tolerant control) systems, two Markov processes were introduced to describe the random failures and the FDI decision behavior separately. The Takagi and Sugeno fuzzy model was employed to represent a nonlinear active FTC system with norm-bounded uncertainties. Based on the parallel distributed compensation scheme, a method for the design of a fuzzy control law such that the closed-loop fuzzy system is robustly stochastically stable, was proposed. The sufficient condition for the existence of a robust and fault tolerant control law was given in terms of linear matrix inequalities, which can be solved efficiently by using the existing LMI (linear matrix inequality) optimization techniques. The latter truck-trailer simulation results show the effectiveness of the proposed method.