SUMMARYIn this paper, we present a new approach for suppression of residual vibrations in point-to-point motions based on lifted iterative learning control (ILC). The approach is to add a signal to the command input during the point-to-point motion in order to compensate for residual vibrations. A special form of ILC with separate actuation and observation time windows is shown to converge to the required signal. Subsequently, we present ILC control strategies for residual vibration suppression in which convergence and performance specifications can be designed separately. Additionally, the designed controllers have the capability to constrain the amplitude of the command signal. The presented strategies are demonstrated on a flexible system and shown to be successful in the suppression of residual vibration while minimizing the maximum amplitude of the command signal.
Abstract-Iterative Learning Control (ILC) is a control strategy to improve the performance of digital batch repetitive processes. Due to its digital implementation, discrete time ILC approaches do not guarantee good intersample behavior. In fact, common discrete time ILC approaches may deteriorate the intersample behavior, thereby reducing the performance of the sampled-data system. In this paper, a generally applicable multirate ILC approach is presented that enables to balance the at-sample performance and the intersample behavior. Furthermore, key theoretical issues regarding multirate systems are addressed, including the time-varying nature of the multirate ILC setup. The proposed multirate ILC approach is shown to outperform discrete time ILC in a realistic simulation example.
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