Neural Sliding Mode Adaptive PD Tracking Control of Omnidirectional Mobile Robots

Abstract

A proportional plus derivative (PD) adaptive tracking control strategy based on neural sliding mode is proposed for the interference of unknown factors in the mathematical model of four-wheel omnidirectional robots. Firstly, the dynamics model of the robot is analyzed. Secondly, the backstepping trajectory tracking controller is used to obtain the virtual velocity, and the PD controller is designed based on the error between the virtual input and the actual input. Then, the neural network is used to approximate the uncertainty in the dynamics model, and the stability of the system is proved by the Lyapunov theorem. Simulation and experimental results show that the control strategy is effective.

Keywords

• Trajectory tracking;Omnidirectional mobile robot;Neural network adaptive control;PD control