Title :
A Design Method of Extended Generalized Minimum Variance Control Based on State Space Approach by Using a Genetic Algorithm
Author :
Yanou, Akira ; Deng, Mingcong ; Inoue, Akira
Author_Institution :
Fac. of Eng., Okayama Univ., Okayama, Japan
Abstract :
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. The extended controller has a new design parameter which can design the controller poles without changing the closed-loop poles, and the genetic algorithm is applied to find the new design parameter and select the controller poles.
Keywords :
closed loop systems; control system synthesis; genetic algorithms; poles and zeros; state-space methods; closed-loop poles; controller design; controller poles; extended generalized minimum variance control; genetic algorithm; state space approach; Aerospace industry; Algorithm design and analysis; Design engineering; Design methodology; Electrical equipment industry; Genetic algorithms; Genetic engineering; Industrial control; Polynomials; State-space methods;
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
DOI :
10.1109/ICICIC.2009.7
