Induction motor drive's parameters identification using genetic algorithms

2012 ◽  
Author(s):  
Roman Yu. Tkachuk ◽  
Alexander S. Glazyrin ◽  
Vladimir I. Polichshuk
Keyword(s):  
Genetic Algorithms ◽  
Induction Motor ◽  
Parameters Identification

Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm

2021 ◽  
Author(s):  
Che-Hang Cliff Chan
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Search Space ◽  
Parameters Identification ◽  
Experimental Results ◽  
Adaptive Search ◽  
Real Coded Genetic Algorithm ◽  
Hysteresis Modeling ◽  
Convergence Performance ◽  
Solution Accuracy

The thesis presents a Genetic Algorithm with Adaptive Search Space (GAASS) proposed to improve both convergence performance and solution accuracy of traditional Genetic Algorithms(GAs). The propsed GAASS method has bee hybridized to a real-coded genetic algorithm to perform hysteresis parameters identification and hystereis invers compensation of an electromechanical-valve acuator installed on a pneumatic system. The experimental results have demonstrated the supreme performance of the proposed GAASS in the search of optimum solutions.

Parameter identification of induction motor model using genetic algorithms

1998 ◽  
Vol 145 (6) ◽  
pp. 587-593 ◽  
Author(s):  
F. Alonge ◽  
F.M. Raimondi ◽  
G. Ferrante ◽  
F. D'Ippolito
Keyword(s):  
Genetic Algorithms ◽  
Parameter Identification ◽  
Induction Motor ◽  
Motor Model
Sign in / Sign up

Export Citation Format

Share Document