Synthesis of Mechanism for single- and hybrid-tasks using Differential Evolution

TL;DR

This paper demonstrates the use of differential evolution for the optimal synthesis of planar mechanisms, including hybrid-tasks and Ackerman mechanisms, improving efficiency by manipulating individuals and applying transformations.

Contribution

It introduces a novel technique for mechanism synthesis using differential evolution, addressing order defect issues and enhancing search efficiency with transformation-based initial populations.

Findings

Successfully synthesized mechanisms for hybrid-tasks, path, and motion generation

Solved order defect problem by manipulating individuals in the search space

Increased evolutionary algorithm efficiency through transformation techniques

Abstract

The optimal dimensional synthesis for planar mechanisms using differential evolution (DE) is demonstrated. Four examples are included: in the first case, the synthesis of a mechanism for hybrid-tasks, considering path generation, function generation, and motion generation, is carried out. The second and third cases pertain to path generation, with and without prescribed timing. Finally, the synthesis of an Ackerman mechanism is reported. Order defect problem is solved by manipulating individuals instead of penalizing or discretizing the search space for the parameters. A technique that consists in applying a transformation in order to satisfy the Grashof and crank conditions to generate an initial elitist population is introduced. As a result, the evolutionary algorithm increases its efficiency.