Experimentally verified generalized KYP Lemma based iterative learning control design

摘要

This paper considers iterative learning control algorithm design for~plants modeled by discrete linear dynamics using repetitive process stability theory. The resulting one step linear matrix inequality based design produces a~stabilizing feedback controller in~the~time domain and a~feedforward controller that guarantees convergence in the~trial-to-trial domain. Additionally, application of the~generalized Kalman-Yakubovich-Popov (KYP) lemma allows a~direct treatment of finite frequency range performance specifications. To support the algorithm development, the results from an experimental implementation are given, where the performance requirements include specifications over~various finite frequency ranges.