A genetic algorithm based optimisation method for iterative learning control systems - Hatzikos, V.; Owens, D. (RoMoCo'02 : proceedings of the third International Workshop on Robot Motion and Control, 2002)
In this paper genetic algorithms are proposed as a method to implement optimality based iterative learning control algorithms. The strength of the proposed method is that it can cope with nonlinearities and hard constraints in the problem definition whereas most of the existing algorithms would fail. Simulation examples show that this approach results in fast convergence for linear plants.