Accuracy-Based Architecture Optimization of a 3-DOF Parallel Kinematic Machine

Qingsong Xu, Yangmin Li
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引用次数: 4

Abstract

In this paper, the architectural parameters optimization of a three degree-of-freedom (DOF) parallel kinematic machine (PKM) with three PUU (prismatic-universal-universal) links is performed using the efficient particle swarm optimization (PSO) to achieve the best accuracy characteristics. The error transformation matrix (ETM) is derived based on the differentiation of kinematic equations, and the lowest value of the maximum singular value of the ETM over a usable workspace is considered as an error performance index for the optimal design. To emphasize the efficiency of the PSO method, both the traditional direct search method and the genetic algorithm (GA) are compared with it. The simulation results demonstrate that the PSO is the best method for the optimization, and the analysis results are valuable in designing and controlling a 3-PUU PKM for machine tool applications
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基于精度的三自由度并联机构结构优化
本文采用高效粒子群算法(PSO)对三自由度并联机构的结构参数进行优化,以获得最佳精度特性。基于运动学方程的微分导出了误差变换矩阵(ETM),并将ETM在可用工作空间上的最大奇异值的最小值作为优化设计的误差性能指标。为了强调粒子群算法的有效性,将传统的直接搜索方法和遗传算法(GA)进行了比较。仿真结果表明,粒子群算法是最佳的优化方法,分析结果对机床用3-PUU PKM的设计和控制具有一定的参考价值
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