Adaptive Fuzzy Sliding Mode Control Algorithm for a Non-Affine Nonlinear System

This paper concerns the design of robust controller for a nonlinear system that can be represented or approximated in a non-affine form. The control algorithm is based on sliding mode control that incorporates a fuzzy tuning technique, and it superposes equivalent control, switching control, and fuzzy control. An equivalent control law is firstly designed based on a nominal system model that was obtained by using curve fitting techniques under MATLAB. Switching control is then added to guarantee that the state reaches the sliding surface in the presence of parameter and disturbance uncertainties. Also, fuzzy tuning schemes, which can be supported by learning techniques derived from neural networks, are employed to improve control performance and to reduce chattering in the sliding mode. To verify the performance of this controller, an experimental platform of a pneumatically actuated top-guided single-seated control valve, which belongs to a classical complex nonlinear system, was constructed. Also, the experimental results show that high performance and attenuated chatter are achieved and thus verify the validity of the proposed control approach to dynamic systems characterized by severe uncertainties.