Abstract
A new learning servo system with a multirate sampling learning compensator is proposed. It reduces memory size remarkably, compared with the conventional learning servo system, and is especially suitable for a commercial application. The developed learning compensator includes two samplers and a digital filter in the input part of it. The first sampler and the digital filter operate at short sampling intervals. The second sampler samples the output of the digital filter at long sampling intervals. The proposed multirate sampling learning servo system achieves excellent robustness to disturbances by using small memory size, and is verified by applying it to a speed and phase control system of a DC motor.
