Path tracking control for a wheeled mobile robot by integrating neural dynamics with adaptive approach

A path tracking control method for a wheeled mobile robot is presented, which combines adaptive approach and neural dynamics to force the robot to track a predefined path. A kinematic controller is introduced to the mobile robot; the control law of which is developed by the model reference adaptive method for ensuring the robot velocity asymptotically approaching to the desired velocity in uncertain system dynamics. To handle the jump-problem between speed and torque, a neural dynamic model is integrated with the above mentioned controls scheme; the stability of the combined system is analyzed by using Lyapunov theory. Simulation results illustrate the effectiveness of the proposed control scheme.