用改进的粒子群算法求解并联6自由度平台的最大误差

Solution on the maximum error of parallel 6-DOF platform using the improved particle swarm algorithm

最大误差是评价并联6自由度平台性能的重要指标,提出了改进的粒子群算法来求解最大误差。首先借助矩阵微分法求出平台误差表达式,将最大误差作为优化目标函数,除了各结构参数误差外,还将平台的位置和姿态列入优化变量。在标准粒子群算法中引入非线性变化权重和变异操作来保证全局收敛并提高收敛精度。实例计算表明该方法的有效性,可用于平台设计阶段的误差预测。

Maximum error is an important index for evaluating the performance of parallel 6-DOF platform, an improved particle swarm optimization algorithm （ PSO ） was put forward to solve the maximum error. Firstly by virtue of matrix differential algorithm to find the error expression of platform and than let the maximum error to be acted as the objective function, besides the parametric errors of each structure, position and posture of the platform were being arranged into the optimized variables as well. By introducing thenonlinear variation weight and mutational operation into the standard particle swarm algorithm to ensuring the overall convergence and enhance the accuracy of convergence. The effectiveness of this method was indicated by a calculation of living example, which can be applied to the error prediction in the designing stage of platform.