Trajectory tracking control for a nonholonomic mobile robot using an improved ILC

This paper develops a kinematic path-tracking algorithm for a nonholonomic mobile robot using an improved iterative learning control (I-ILC) technique. The proposed algorithm produces a velocity command to the wheeled robot, in addition, the state disturbances and measurement noises are taken into consideration. In the learning rule, an adjustable parameter is defined and by adjusting this parameter we can obtain the best learning rule. From the simulation results we find that the system outputs and control inputs are bounded to converge to the desired values. The MATLAB software is used for simulation to verify the feasibility and validity of the proposed learning algorithm.