Decentralized adaptive PI fault tolerant tracking control for strong interconnected nonlinear systems subject to unmodeled dynamics and actuator faults

In this study, a novel decentralized adaptive proportional–integral (PI) fault tolerant tracking control strategy is proposed for a class of strong interconnection nonlinear systems with unmodeled dynamics and actuator faults. The adverse effects generated by unmodeled dynamics could be eliminated by introducing a dynamic signal and the multiplicative actuator faults could be dealt with by using adaptive control technique. In addition, broad learning system (BLS) scheme is used to approximate the unknown nonlinear functions and additive actuator faults, the minimal-learning-parameter (MLP) scheme is used in this study to reduce the number of adaptive update parameters, which resltus in less computation overhead. The decentralized adaptive PI fault tolerant tracking controller including a switching compensation mechanism is designed for the considered interconnected systems, such that all the signals in the closed-loop systems are uniformly ultimately bounded (UUB) and the tracking errors converge to a small residual set. In the end, a chemical reactor example is utilized to illustrate the feasibility and significance of the designed control scheme.