Neural Network Control of a Four-Wheeled Mobile Robot Subject to Wheel Slip

The paper presents design of a control structure that enables integration of a kinematic and a neural network controller for a four-wheeled mobile robot subject to wheels slip. The controller is proposed to make the actual velocity of the wheeled mobile robot reach the desired velocity, although the wheeled mobile robot is even with system uncertainties and disturbances. The proposed tracking control system consists of: the kinematic and proportional controller, the neural approximated term and robust term derived from the stability analysis carried out using Lyapunov stability theorem. The proposed control system works on-line, weights adaptation is realized in every discrete step of the control process, and a preliminary learning phase of neural networks weights is not required. Computer simulation was conducted to illustrate performance of the control system.