Open Access
ARTICLE
Synthesis Optimization of Piezo Driven Four Bar Mechanism Using Genetic Algorithm
Laith Sawaqed1, Khaled S. Hatamleh1,2, Mohammad A. Jaradat1,2, Qais Khasawneh1,3
1 Mechanical Engineering Department, Jordan University of Science & Technology, P.O.Box 3030 Irbid, Jordan
kshh@just.edu.jo, majaradat@just.edu.jo, qakhasawneh@just.edu.jo
2 Mechanical Engineering Department, American University of Sharjah, P.O. Box (2666) Sharjah, UAE
khatamleh@aus.edu, mjaradat@aus.edu
3 Electromechanical Engineering technology department, Institute of Applied Technology, Abu-Dhabi, UAE
Qais.khasawneh@adpoly.ac.ae
* Corresponding Author: Laith Sawaqed,
Intelligent Automation & Soft Computing 2018, 24(3), 507-515. https://doi.org/10.31209/2018.100000039
Abstract
Over the past few years, there has been a growing demand to develop efficient
precision mechanisms for fine moving applications. Therefore, several
piezoelectric driven mechanisms have been proposed for such applications. In
this work an optimal synthesis of a four-bar mechanism with three PEAs is
proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are
formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first
used to obtain a synthesis solution for the mechanism regardless of power
consumption. Then another Genetic Algorithm Minimum Power Synthesis
method (GAMPS) is used to obtain the synthesis solution of minimum power
consumption. For that purpose, the study performs simulation investigation of
the aforementioned algorithms for each point along sinusoidal and kidney
shaped paths of motion. Results show capability of both methods in obtaining a
synthesis solution. However, GAMPS outperformed GAS in terms of driving
power consumption as it is minimized by 99% ratio.
Keywords
Cite This Article
L. Sawaqed, K. S. Hatamleh, M. A. Jaradat and Q. Khasawneh, "Synthesis optimization of piezo driven four bar mechanism using genetic algorithm,"
Intelligent Automation & Soft Computing, vol. 24, no.3, pp. 507–515, 2018.