Adaptive robust iterative learning control for uncertain robotic systems

In this paper, the uncertain model of the robotic system is decomposed into repetitive and non-repetitive parts, and the norm model of the system is taken into account. By using the Lyapunov method, an adaptive robust iterative learning control scheme is presented for the robotic system with both structured and unstructured uncertainty, and the overall stability of the system in the iteration domain is established. In the scheme the bound parameters estimated as well as the iterative learning control input are adjusted in the iteration domain. The validity of the scheme is illustrate through a simulation example.