In this paper, we propose a modified version of the Proportional Integral Derivative (PID)-type iterative learning algorithm. It is very simple to implement on a digital control device for tracking control a continuous-time system. Matlab software is used to model and simulate control algorithms. The simulative application of it to control a gearing transmission system, such that its output response follows the desired trajectory, is then carried out computationally. Obtained studying results proves that this proposed iterative learning algorithm has provided a good output tracking behavior as expected and which is robust in the sense of reducing external disturbance effects.

In this paper, Iterative Learning Control (ILC) combined with a Proportional Derivative (PD) regulator is proposed to deal with the problem of designing a control signal for motion control systems. The main idea in iterative learning control is to gradually improve the performance of the system by exploiting data from the previous iterations. The learning control algorithm can obtain a better tracking control performance for the next run and hence outperforms conventional control approaches such as Proportional Integral Derivative (PID) controller and feedforward control. The main area of application for ILC is control of industrial robots and CNC machine tool, printing, and other industrial applications. The learning algorithms can also be used in combination with other control techniques. For example, learning feedforward control is designed in the first iteration. Then iterative learning control is applied to improve performance in the subsequent iterations. In addition, the conventional feedback regulator is designed in combination with iterative control to deal with uncertainty. Simulation results demonstrate the potential benefits, sensitivity and robustness of the proposed method.