Title :
Improved differential evolution algorithm and its application in induction motor motion
Author :
Cai, Mingshan ; Li, Xiaofeng ; Yang, Minsheng ; Zhang, Meiying
Author_Institution :
Electr.&Inf. Eng. Sch., Hunan Univ. of Arts & Sci., Changde, China
Abstract :
An improved differential evolution algorithm for solving nonlinear equations of electrical motor system is explored. The algorithm is to convert equations into an optimization problem and, by keeping consideration of the evolution process and adopting dynamic parameters adjusting mechanism, the algorithm can improve searching efficiency and implement real-time surveillance for population overlapping. The chaos searching strategy is used for overlapping individual to further improve the ability of global optimization. Analysis results of induction motor motion parameters show that the improved differential evolution algorithm proposed in this paper has high efficiency and powerful global optimization searching ability.
Keywords :
electric motors; induction motors; nonlinear equations; optimisation; surveillance; chaos searching strategy; differential evolution algorithm; dynamic parameters; electrical motor; induction motor motion; nonlinear equations; optimization problem; population overlapping; real-time surveillance; Algorithm design and analysis; Art; Chaos; Convergence; Genetic algorithms; Induction motors; Intelligent transportation systems; Iterative algorithms; Nonlinear equations; Power engineering and energy; chaos; differential evolution; induction motor motion; intelligent optimization; non-linear equations;
Conference_Titel :
Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-4544-8
DOI :
10.1109/PEITS.2009.5406946