Fuzzy Neural Network Control of a Flexible Robotic Manipulator Using Assumed Mode Method

Abstract

In this paper, in order to analyze the single-link flexible structure, the assumed mode method is employed to develop the dynamic model. Based on the discrete dynamic model, fuzzy neural network (NN) control is investigated to track the desired trajectory accurately and to suppress the flexible vibration maximally. To ensure the stability rigorously as the goal, the system is proved to be uniform ultimate boundedness by Lyapunov's stability method. Eventually, simulations verify that the proposed control strategy is effective, and the control performance is compared with the proportion derivative control. The experiments are implemented on the Quanser platform to further demonstrate the feasibility of the proposed fuzzy NN control.