以6自由度空间绳牵引并联机器人工作空间体积、最小索力和全局灵巧度为优化目标,在保证绳索张力范围的前提下建立了多目标优化的数学优化模型.采用神经网络-遗传算法求得优化的3组满意解,并采用灰色聚类法选择多目标优化时的权重系数.仿真结果表明该优化方法可以有效地实现结构的优化,为同类绳牵引并联机器人的设计提供了有益的参考
This paper investigates the multi-object optimization for a spatial 6-DOF (degree-of-freedom) cable-driven parallel manipulator. The optimization based on an NN (neural network)-genetic algorithm was carried out respectively with regarded to workspace volume, the minimum tension and global dexterity index, then three groups of satisfactory solutions were obtained. Furthermore, the weight coefficients for the multi-object optimization model were gained through the grey clustering method. The results show that the NN-genetic algorithm is effective for the structural optimization and can provide a useful reference for the optimal design of similar manipulators
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