Adaptive Fuzzy Backstepping Dynamic Surface Control of Uncertain Nonlinear Systems Based on Filter Observer

In this paper, a novel adaptive fuzzy backstepping output feedback control scheme is proposed for a class of single-input single-output (SISO) uncertain nonlinear systems without measurements of states. Fuzzy logic systems (FLS) are used to tackle unknown nonlinear functions, and the adaptive fuzzy output feedback controller is constructed by combining fuzzy filters observer design and the dynamic surface control (DSC) technique. It is proved that the proposed adaptive fuzzy 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 origin. Two key advantages of our scheme are that (i) the proposed control method does not require that all the states of the system be measured directly, and (ii) the problem of “explosion of complexity” is avoided. Finally, two simulations examples are included to illustrate the effectiveness of the proposed approach.