Iterative Learning Control for Path-Following Tasks With Performance Optimization

The classical problem setup of iterative learning control (ILC) is to enforce tracking a reference profile specified at all time points in the fixed task duration. removal specification releases significant design freedom how path followed but has not been fully exploited literature. This article unlocks this extra by formulating ILC description handle repeated path-following tasks, e.g., welding and laser cutting, which aim following given “spatial” defined output space without any temporal information. general reformulated for with inclusion an additional performance index, class piecewise linear paths characterized setup. A two-stage framework proposed solve yields comprehensive algorithm based on update gradient projection update. verified gantry robot experimental platform demonstrate its practical efficacy robustness against model uncertainty.