Adaptive fuzzy neural networks control for switched nonlinear systems

This paper is concerned with the tracking control problem for a class of single input and single output (SISO) uncertain switched nonlinear systems under arbitrary switchings. The proposed approach is explored by employing fuzzy neural networks (FNN) to tackle unknown nonlinear functions and combining the adaptive backstepping technique with adaptive fuzzy control design. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. A numerical example is provided to illustrate the effectiveness of the proposed approach.