Direct adaptive fuzzy position controller for an electropneumatic actuator: Design and experimental evaluation

Abstract

This paper proposes a direct adaptive fuzzy position controller for an electropneumatic actuator. This control approach is based on the estimation of an ideal inverse dynamic control, which is capable of satisfying the control objectives in terms of tracking desired trajectories and stability. For this purpose, a fuzzy system is used to approximate as best as possible this ideal inverse dynamic control. The adjustable parameters of the used fuzzy system are updated online with a stable adaptation law. This latter is developed in order to minimize the error between the unknown ideal inverse dynamic control and the used fuzzy controller. The general non-affine model of the controlled actuator is used to develop the control law and its adaptation mechanism, meaning that the presented adaptive fuzzy position controller does not rely on a physical model of the pneumatic actuator. The stability of the closed-loop system is performed using a Lyapunov approach. Finally, real-time experimental results are presented to show the performances of the proposed position controller.