Title :
Multi-criteria control system parameters optimization based on genetic algorithm
Author :
Zhimin, Yang ; Xu, Wang ; Xianyi, Zhuang
Author_Institution :
Dept. of Control Eng., Harbin Inst. of Technol., China
fDate :
6/22/1905 12:00:00 AM
Abstract :
Presents a multi-parameter optimization method based on the solution of the multi-criteria optimization problem using a multi-objective constrained genetic algorithm. By incorporating the fuzzy rules in the fitness assignment procedure, the GA can simultaneously handle multiple design objectives and constraints with relative importance. Simulation results show that this algorithm can obtain acceptable solutions satisfying all constraints
Keywords :
MIMO systems; control system synthesis; fuzzy set theory; genetic algorithms; fitness assignment procedure; fuzzy rules; multi-criteria control system; multi-criteria control system parameters optimization; multi-objective constrained genetic algorithm; Constraint optimization; Control engineering; Control system synthesis; Control systems; Design optimization; Genetic algorithms; Nonlinear control systems; Optimization methods; Robust stability; Steady-state;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.860053