Optimization of Variable-Capacitance Micromotor Using Genetic Algorithm

Author

Ketabi, Abbas ; Navardi, Mohammad Javad

Author_Institution

Dept. of Electr. Eng., Univ. of Kashan, Kashan, Iran

Volume

20

Issue

2

fYear

2011

fDate

4/1/2011 12:00:00 AM

Firstpage

497

Lastpage

504

Abstract

In this paper, the optimization shape of a polysilicon variable-capacitance micromotor (VCM) was determined using genetic algorithm (GA). The optimum goal of the algorithm was found for a maximum torque value and a minimum torque ripple, following changing the geometric parameters. The optimization process was carried out using a combination of GA and finite-element method (FEM). The fitness value was calculated by FEM analysis using COMSOL3.4, and the GA was realized by MATLAB7.4. The proposed method has been applied for the two case studies, and it has been also compared with successive sampling method. The results show that the optimized micromotor using GA had a higher torque value and a lower torque ripple, indicating the validity of this methodology for VCM design.

Keywords

finite element analysis; genetic algorithms; microactuators; micromotors; COMSOL3.4; FEM analysis; MATLAB7.4; finite-element method; fitness value; genetic algorithm; geometric parameters; maximum torque value; microelectromechanical systems actuator; minimum torque ripple; optimization shape; polysilicon variable-capacitance micromotor; Finite element methods; Gallium; Micromotors; Optimization; Rotors; Stators; Torque; Finite-element method (FEM); genetic algorithm (GA); micromotor optimization; variable-capacitance micromotor (VCM);

fLanguage

English

Journal_Title

Microelectromechanical Systems, Journal of

Publisher

ieee

ISSN

1057-7157

Type

jour

DOI

10.1109/JMEMS.2011.2105247

Filename

5711627