A novel backstepping adaptive control approach based on fuzzy neural network disturbance observer

A fuzzy neural network disturbance observer (FNNDO) is developed and a backstepping adaptive control approach combined with FNNDO is presented for a general class of strict-feedback nonlinear systems with a wide class of uncertainties that are not linearly parameterized and do not have any prior knowledge of the bounding functions. FNNDO is used to approximate the unknown uncertainties online, and the systematic framework for adaptive controller design is given by backstepping control approach. All signals in the closed loop system can be guaranteed uniformly ultimately bounded by Lyapunov approach. We show in our analysis and simulation that FNNDO has strong approximation ability and fuzzy linguistic interpretation. High control precision for the control system can be achieved.