Fuzzy Neural Networks Control of Flexible Robotic Manipulator Based on Lumped Spring-Mass Model

Abstract

In this research, the focus is on the adaptive fuzzy neural networks (NNs) control of the single-link flexible robot manipulator, which achieves accurate trajectory tracking and improves the speed of position tracking. Firstly, in order to establish a single-link flexible model, the lumped spring-mass method and Lagrangian equation are used. Secondly, a full-state feedback control is proposed. Aiming at achieving the control objective, the Lyapunov stability method proves that the closed-loop system is uniformly ultimately bounded. Finally, Numerical simulations are carried out to verify the performance of the fuzzy NNs control. Furthermore, the control performance is compared with the proportion derivative control.