Parametric Iterative Learning Control: A Method for Adaptation of Feedforward Control, and Application to Gearshift Control

摘要

A framework for parametric iterative learning is introduced in this study, the underlying philosophy of which entails parameterization of feedforward control inputs in the form of look-up tables as functions of the trial-varying aspects of repetitive system operation. The current study focuses on tracking of a trial-varying reference trajectory in the presence of trial-varying external disturbances. Theoretical results for convergence are presented, and the proposed method of parametric learning is validated numerically for the application of adaptive control of gearshift controllers.