Hybrid adaptive fuzzy control for uncertain MIMO nonlinear systems with unknown dead-zones

In this paper, a hybrid adaptive fuzzy control approach is proposed for a class of uncertain multiple-input and multiple-output (MIMO) strict-feedback nonlinear systems with unknown dead-zones. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a serial-parallel estimation model is established. Based on the adaptive backstepping dynamic surface control (DSC) technique, and utilizing the bounds of the dead-zone slopes and the prediction errors between the system model and the serial-parallel estimation model, a new robust adaptive fuzzy backstepping controller with the composed parameters adaptive laws is developed. The proposed control method can not only overcome the problem of “explosion of complexity” inherently existing in traditional backstepping design methods, but also improve the control performance. It is proved that all the signals of the closed-loop systems are bounded and the system output can follow the given bounded reference signal. A numerical example and simulation comparisons with the existing control methods are provided to show the effectiveness of the proposed approach.