Two-dimensional Systems Based Iterative Learning Control for High-Speed Rack Feeder Systems

Many systems compete the same finite duration task over and over again, where once each is completed the system resets to the starting location and the next execution begins. Each execution is known as a trial and the duration is the trial length. Iterative learning control algorithms have been developed for such systems where the novel feature is the use of information from previous trials to update the control input for application on the next one. This paper uses the 2D systems structure of iterative learning control to design in one step a control law for trial-to-trial error convergence and along the trial transient dynamics. The analysis makes use of the generalized form of the Kalman-Yakubovich-Popov lemma and the design is evaluated in simulation on a high-speed rack feeder model as a prerequisite for experimental validation.