Iterative learning control for constrained nonlinear systems

An iterative learning control method is presented based on the analysis of the constraint to achieve precise tracking control of a class of constrained nonlinear systems over a finite time interval. The learning is done in a feedback configuration formed by the constraint, and the learning law updates the reference input from the plant input of the previous trail. A sufficient condition which guarantees the convergence of the learning is given. From the derivation, we can establish that the bounds of the asymptotic errors is due to the existence of the constraint terms and its Lie derivative with respect to (f, G, k)