Abstract
It is not easy for a typical servo mechanism to track arbitrary velocity profile by linear controllers. Iterative learning control (ILC) scheme can reduce the tracking error through repeated trials to achieve this goal. There are restrictions for using ILC, certain dynamics, e.g. vibrations and disturbances will cause the learning task to fail. Here, a discrete wavelet transform (DWT) is employed to extract unlearnable dynamics. While learnable dynamics is handled by ILC, unlearnable dynamics is regulated by feedback control. It will let ILC become more robust. Within the operational bandwidth, applying DWT based ILC can achieve excellent speed-tracking performance of the servo mechanism under study. This thesis presents a DWT based Iterative learning controller for DC servo motor. An algorithm to design learning gains and feedback gains that guarantees the convergence of learning curve is proposed. Its feasibility is verified through simulations. The effect of disturbances and sensor resolution on the performance of ILC is explored. Experimental platform and the peripheral circuit were devised. ILC is implemented on a Digital Signal Processor (DSP), and the control law is realized on the DC servo system. The experimental results further verify the simulated results. According to the experimental results, DWT based ILC is more robust than general ILC and can let DC servo system to track arbitrary speed profile within the operational bandwidth by iterative learning.