Multiobjective constrained optimal synthesis of planar mechanisms using a new evolutionary algorithm

J.A. Cabrera; F. Nadal; J.P. Muñoz; A. Simon

doi:10.1016/j.mechmachtheory.2006.07.004

Multiobjective constrained optimal synthesis of planar mechanisms using a new evolutionary algorithm

Mechanism and Machine Theory ◽

10.1016/j.mechmachtheory.2006.07.004 ◽

2007 ◽

Vol 42 (7) ◽

pp. 791-806 ◽

Cited By ~ 48

Author(s):

J.A. Cabrera ◽

F. Nadal ◽

J.P. Muñoz ◽

A. Simon

Keyword(s):

Evolutionary Algorithm ◽

Optimal Synthesis ◽

Planar Mechanisms

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Optimal synthesis of mechanisms using repellency evolutionary algorithm

Knowledge-Based Systems ◽

10.1016/j.knosys.2021.107928 ◽

2021 ◽

pp. 107928

Author(s):

Qiujun Huang ◽

Yicheng Yu ◽

Kai Zhang ◽

Shengquan Li ◽

Haibo Lu ◽

...

Keyword(s):

Evolutionary Algorithm ◽

Optimal Synthesis ◽

Synthesis Of Mechanisms

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OPTIMAL SYNTHESIS OF PLANAR MECHANISMS BY PARAMETRIC DESIGN TECHNIQUES

Engineering Optimization ◽

10.1080/03052157608960597 ◽

1976 ◽

Vol 2 (1) ◽

pp. 55-63 ◽

Cited By ~ 1

Author(s):

B. M. KWAK ◽

E. J. HAUG

Keyword(s):

Parametric Design ◽

Optimal Synthesis ◽

Planar Mechanisms ◽

Design Techniques

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Optimal Synthesis of Mechanisms for Path Generation Using Refined Numerical Representation Based Model and AIS Based Searching Method

Journal of Mechanical Design ◽

10.1115/1.1898342 ◽

2004 ◽

Vol 127 (4) ◽

pp. 688-691 ◽

Cited By ~ 13

Author(s):

Yong Liu ◽

Renbin Xiao

Keyword(s):

Synthesis Method ◽

Optimal Synthesis ◽

Numerical Representation ◽

Path Generation ◽

Artificial Immune ◽

Planar Mechanisms ◽

Artificial Immune Network ◽

Synthesis Of Mechanisms ◽

Initial Sampling ◽

Searching Method

This paper presents an optimal synthesis method for path generation of planar mechanisms, in which a new path-description method named refined numerical representation is proposed to define the object function of the optimization model for path generation, and then the artificial immune network searching method is introduced to search candidate solutions. As a result, desired mechanisms can be generated independent of the scale, rotation, and translation transformation as well as sampling uniformity of initial sampling points. Experiment results demonstrate the effectiveness of the approach.

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Turning Functions in Optimal Synthesis of Mechanisms

Journal of Mechanical Design ◽

10.1115/1.4029825 ◽

2015 ◽

Vol 137 (6) ◽

Cited By ~ 6

Author(s):

Fernando Nadal ◽

Juan A. Cabrera ◽

Alex Bataller ◽

Juan J. Castillo ◽

Antonio Ortiz

Keyword(s):

Evolutionary Algorithm ◽

Optimization Algorithm ◽

Optimal Synthesis ◽

Mechanism Synthesis ◽

Synthesis Of Mechanisms

In this paper, we describe the use of turning functions to compare errors between the coupler and the target paths. The main reason to use turning functions is that the measured error does not depend on the mechanism scale or the position and rotation of the fixed link. Therefore, the searching space for the optimization algorithm is reduced. To carry out mechanism synthesis, we use an evolutionary algorithm. The effectiveness of the proposed method has been demonstrated in five synthesis examples.

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