A DESIGN METHOD OF EXTENDED GENERALIZED MINIMUM VARIANCE CONTROL BASED ON STATE SPACE APPROACH BY USING A GENETIC ALGORITHM

作者：Yanou Akira^*; Deng Mingcong; Inoue Akira

来源：International Journal of Innovative Computing Information and Control, 2011, 7(7B): 4183-4194.

• Generalized minimum variance control
• Coprime factorization
• State space
• Genetic algorithm
• Strongly stable

This paper explores a selection method of the design parameter introduced in the extended Generalized Minimum Variance Control (GMVC) based on state space approach by using a genetic algorithm. Its parameter can design the controller poles to be stable without changing the closed-loop poles. That is, a strongly stable system can be obtained. And the genetic algorithm is applied to calculate the design parameter and give the stable controller poles.

• 出版日期2011-7