A design of a strongly stable generalized minimum variance control using a genetic algorithm

This paper proposes a design scheme of generalized minimum variance control (GMVC) having a new design parameter. The design parameter is introduced by applying coprime factorization approach and Youla-Kucera parameterization of stabilizing compensators to a generalized minimum variance controller. And it is selected by using a genetic algorithm so that the controller is designed to be stable. Therefore the proposed method gives a strongly stable system, that is, not only the closed-loop system is stable, but also the controller itself is stable.