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首页> 外文期刊>Mechatronics: The Science of Intelligent Machines >Advanced mechatronic design using a multi-objective genetic algorithm optimization of a motor-driven four-bar system
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Advanced mechatronic design using a multi-objective genetic algorithm optimization of a motor-driven four-bar system

机译：使用多目标遗传算法优化电机驱动四连杆系统的先进机电一体化设计

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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.
机译：在这项工作中，我们提出了一种基于遗传算法的方法来设计机电系统。首先，我们介绍了一种顺序方法，在该方法中，我们针对给定的路径优化了机械的几何形状，然后解决了动力学问题，其中我们考虑了电动机的特性以及机械不同连杆的惯性。测试了几种类型的目标函数。但是，我们表明，由于在优化动力学时会假定几何形状是固定的，因此该顺序方法无法为动力学行为产生令人满意的结果。这导致我们提出了一个全局优化问题，其中同时考虑了该机制的所有参数。然后将问题表示为一种多目标优化，其中同时考虑了几何和动力学。所获得的解决方案形成了所谓的“帕累托阵线”，并针对几种不同的设计条件对其进行了分析。本文还展示了多目标优化方法优于单目标方法的优势。

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