In order to control robot to track the desired trajectory or make it reach the specified target position and pose, a trajectory tracking control model based on the optimized iterative learning algorithm was designed. The interactive application control modules, such as the fourwheel drive WMR mechanical framework and the master control sensor, were combined to process the trajectory signal of the robot and a key dynamic model was established in accordance with the optimization principle of extreme convergence of iterative learning algorithm, so as to realize realtime tracking and control of the trajectory of the robot. Simulation experiments were designed to verify the effectiveness of the optimal iterative learning algorithm for the control of the robot’ s trajectory.