Adaptive Fuzzy Decentralized Control for Nonstrict Feedback Nonlinear Systems With Unmodeled Dynamics

An adaptive fuzzy decentralized control algorithm is developed in this article for interconnected nonlinear large-scale systems with unmodeled dynamics. This method is proposed by applying a fuzzy logic system (FLS) to identify unknown nonlinear functions. In addition, dynamic signals are introduced in design process of the backstepping to compensate the effect of unmodeled dynamics. A novel adaptive state feedback control algorithm is proposed with the help of Lyapunov function. Then, the state feedback control algorithm is extended to the case of output feedback by constructing a fuzzy state observer with FLSs. The large-scale and closed-loop nonlinear system is ensured to be semi-global uniformly ultimately bounded (SGUUB). Apart from this, all signals are guaranteed to be bounded. Both numerical and practical simulation examples are utilized to elaborate the feasibility of the developed control algorithms.