Iterative learning control for systems with input deadzone

Most iterative learning control (ILC) schemes proposed hitherto were designed and analyzed without taking the input deadzone into account. Input deadzone is a kind of nonsmooth and nonaffine-in-input factor widely existing in actuators or mechatronics devices. It gives rise to extra difficulty due to the presence of singularity in the input channels. In this note, we disclose that ILC methodology remains effective for systems with input deadzone that could be nonlinear, unknown and state-dependent. Through rigorous proof, it is shown that despite the presence of the input deadzone, the simplest ILC scheme retains its ability of achieving the satisfactory performance.