ITERATIVE LEARNING CONTROL IN FEEDBACK-SYSTEMS

An iterative learning control method is proposed to achieve precise tracking control of a class of nonlinear systems over a finite time interval. The learning is done in a feedback configuration and the learning law updates the feedforward input from the plant input of the previous trial. A sufficient condition which guarantees the convergence of the learning is given. It is shown that the convergence condition of the learning control in the feedback configuration does not change from the condition in an open-loop configuration. But the learning speed can be improved greatly in the feedback configuration. Employing an input saturator which limits the control input within a reasonable bound, the class of nonlinear systems to which the proposed learning scheme can be applied is extended. The proposed learning control process is applied to the tracking control of a two link robot manipulator, and good tracking performance is obtained in the simulation.