Adaptive fuzzy decentralized control for a class of MIMO large-scale nonlinear state delay systems with unmodeled dynamics subject to unknown input saturation and infinite number of actuator failures

Abstract This paper addresses design of an adaptive fuzzy decentralized fault-tolerant controller for a class of uncertain multi-input multi-output (MIMO) large-scale nonlinear systems with unmodeled dynamics subject to unknown state time-varying delay, external disturbances, unknown input saturation and actuator faults. It is shown that the proposed fault-tolerant control (FTC) scheme can handle infinite number of actuator failures including partial and total loss of effectiveness. System uncertainties have been approximated by the fuzzy logic systems (FLSs). To cope with the unknown state time-varying delay, the Razumikhin lemma has been utilized and unmodeled dynamics has been tackled by introducing a dynamical signal. To avoid high computational burden, the dynamic surface control (DSC) technique has been used and the number of adaption laws has been reduced by updating the maximum norm of fuzzy weight vectors of each subsystem. It has been shown that all closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB) and the output tracking errors converge to a small neighborhood of the origin by choosing the design parameters appropriately. Simulation results demonstrate the effectiveness of the proposed control scheme.