Advanced mechatronic design using a multi-objective genetic algorithm optimization of a motor-driven four-bar system

In this work we present a genetic algorithm based method to design a mechatronic system. First, we present the sequential approach where we optimize the geometry of the mechanism, for a given path, and then solve the dynamic problem where we take into account the characteristics of the motor along w...

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Bibliographic Details
Published in:Mechatronics (Oxford) Vol. 17; no. 9; pp. 489 - 500
Main Authors: Affi, Zouhaier, EL-Kribi, Badreddine, Romdhane, Lotfi
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.11.2007
Elsevier Science
Subjects:
Advanced mechatronic design
Applied sciences
Drives
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Genetic algorithms
Linkage mechanisms, cams
Mechanical engineering. Machine design
Mechanism synthesis
Multi-objective optimization
Physics
Solid dynamics (ballistics, collision, multibody system, stabilization...)
Solid mechanics
Advanced mechatronic design
Multi-objective optimization
Mechanism synthesis
Genetic algorithms
Mechatronics
Genetic algorithm
Four bar mechanism
Linkage mechanism
Multiobjective programming
Experimental study
Optimization
Light emitting diode
ISSN:0957-4158, 1873-4006
Online Access:Get full text
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Summary:In this work we present a genetic algorithm based method to design a mechatronic system. First, we present the sequential approach where we optimize the geometry of the mechanism, for a given path, and then solve the dynamic problem where we take into account the characteristics of the motor along with the inertia of the different links of the mechanism. Several types of objective functions are tested. We show, however, that this sequential method does not yield acceptable results for the dynamic behavior due to the fact that the geometry is assumed fixed when optimizing the dynamics. This led us to formulate a global optimization problem where all the parameters of the mechanism are considered simultaneously. The problem is then presented as a multi-objective optimization one where the geometry and the dynamics are considered simultaneously. The obtained solutions form what is called a “Pareto front” and they are analyzed for several different design conditions. This paper also shows the advantages of a multi-objective optimization approach over the single-objective one.
ISSN:0957-4158
1873-4006
DOI:10.1016/j.mechatronics.2007.06.003