Adaptive iterative learning control for systems with nonlinearities

In this paper, we consider the problem of ILC when it deals with systems with piecewise linear nonlinearities. Most of actuators have nonlinear characteristics such as hysteresis, backlash, dead-zone or piecewise linear nonlinearities. These nonlinearities make controller design difficult, specifically when their parameters are not known. Iterative learning control, (ILC), uses an iterative algorithm to track a fixed reference output signal in a specific period of time. We use the results of iterative learning control design based on 2D system theory and nonlinearity inverse method to compensate the effect of the actuator nonlinearity.