Title :
Design Optimization of Polysilicon Electrostatic Micromotor Based on Genetic Algorithm
Author :
Lin, Zhi-Wei ; Li, Jun ; Zhang, Bai-Hai ; Di, Xin
Author_Institution :
Dept. of Autom. Control, Beijing Inst. of Technol., Beijing, China
Abstract :
To get the optimization shape of polysilicon electrostatic micromotor, the method of the combination of genetic algorithm (GA) and FEM analysis is studied. Fitness value is calculated by ANSYS, and the genetic algorithm is realized by APDL language. Simple genetic algorithm is improved by self-adaptive big mutation operation, and the big mutation operation is utilized to avoid premature when the number of population is small. A good optimization result is get. Then a comparison of GA and optimization method in ANSYS is showed. The results show that GA is more effective than zero/first order optimization method in ANSYS.
Keywords :
electrical engineering computing; electrostatic motors; finite element analysis; genetic algorithms; silicon; ANSYS; APDL language; FEM analysis; design optimization; fitness value; genetic algorithm; optimization shape; polysilicon electrostatic micromotor; self-adaptive big mutation operation; Clouds; Design optimization; Electrostatic analysis; Genetic algorithms; Genetic mutations; Geometry; Micromotors; Optimization methods; Stators; Torque; ANSYS; genetic algorithm; polysilicon electrostatic micromotor; self-adaptive big mutation;
Conference_Titel :
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location :
Manchester
Print_ISBN :
978-0-7695-3634-7
DOI :
10.1109/ICIC.2009.238
