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A COMBINED GENETIC ALGORITHM-FUZZY LOGIC METHOD (GA-FL) TO DESIGN A 6 BARS PLANAR MECHANISM

机译:组合遗传算法-模糊逻辑方法(GA-FL)设计6杆平面机构

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摘要

This work deals with solution methods of optimal synthesis of planar mechanisms. A searching procedure presents a combined genetic algorithm - fuzzy logic method to solve the problem of path generation in mechanism synthesis. Previous works, dealing with the same problem and using the genetic algorithm method, suffered from the lack of precision, especially for large domain problems. The proposed method is made of a classical genetic algorithm coupled with a fuzzy logic controller (GA-FL). This controller monitors the variation of the design variables during the first run of the genetic algorithm and modifies the initial bounding intervals to restart a second round of the genetic algorithm. For both of these runs, we limited the number of generations to roughly half of the number found in the literature, without reducing the accuracy of the final solution. Compared to previous works on the same problem, our method proved to be more efficient in finding the optimal mechanism. The effectiveness of the proposed method has been demonstrated on a six bars synthesis example.
机译:这项工作涉及平面机制的最佳综合的解决方法。一种搜索过程提出了一种组合遗传算法-模糊逻辑方法来解决机构综合中的路径生成问题。以前的处理相同问题并使用遗传算法方法的工作缺乏精确性,特别是对于大范围问题。所提出的方法是由经典遗传算法与模糊逻辑控制器(GA-FL)结合而成的。该控制器在遗传算法的第一次运行期间监视设计变量的变化,并修改初始边界间隔以重新开始遗传算法的第二轮。对于这两个运行,我们将代数限制为文献中找到的代数的大约一半,而不会降低最终解决方案的准确性。与以前对相同问题的研究相比,我们的方法被证明在寻找最佳机理方面更为有效。该方法的有效性已在六棒合成示例中得到了证明。

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