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Iterative learning control has been especially developed for systems defined over a finite duration that repeat the same task. Each execution is known as a trial, or pass, and the sequence of operations is that a trial is completed, the system is then reset to the starting location, and the next pass begins. The novel feature of this control law design method is to use information from the previous...
This paper uses 2D control systems theory to develop robust iterative learning control laws for linear plants with experimental validation on a gantry robot used for `pick and place' operations commonly found in industries such as food processing. In particular, the stability theory for linear repetitive processes provides the setting for analysis and this allows design to take account of trial-to-trial...
In this paper, we present the design of a robust Iterative Learning Control (ILC) algorithm for a single flexible link in the presence of parametric uncertainty. The robust ILC design is formulated as a min-max problem with a quadratic performance index. An upper bound of the worst-case performance is employed in the min-max problem. Applying Lagrange duality to the min-max problem, we can reformulate...
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