Title :
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
fDate :
4/1/2011 12:00:00 AM
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);
Journal_Title :
Microelectromechanical Systems, Journal of
DOI :
10.1109/JMEMS.2011.2105247