Second-order iterative learning control for scaled setpoints

Iterative learning control (ILC) is a control technique for systems subject to repetitive setpoints or disturbances. However, in many applications, the setpoint is not strictly repetitive, and the learning process should start all over from the beginning if the setpoint changes. In this brief, point-to-point movements with different magnitudes will be considered, which are constructed by scaling a nominal setpoint. Second-order ILC with an adaptive low-pass filter in the trial domain is used to accurately track these scale varying setpoints under the influence of disturbances that are either repetitive or experience the same scaling as the setpoint. Experiments have been carried out to validate the proposed method.