一种基于模糊决策的绳驱并联机构逆运动学算法

An Inverse Kinematics Algorithm of Cable-driven Parallel Mechanism Based on Fuzzy Decision

由于绳索数目大于运动自由度,具有冗余驱动的特点,且绳索长度求解关节角度的逆运动学过程具有高度非线性特点,难以求得解析解,同时存在测量干扰时数值计算结果误差较大。为解决该问题,设计2自由度绳驱并联平台样机,建立机构的运动学模型,基于模糊决策设计一种抗干扰的绳驱并联机构逆运动学算法。该逆运动学算法将驱动空间和关节空间进行模糊化,由绳索长度计算关节角度,从而抑制了过约束计算对测量噪声的敏感性。利用数值仿真技术对该算法和传统牛顿迭代算法进行对比,结果表明:该逆运动学算法具有较高的计算准确性和稳定性,可以用于绳驱并联机构的运动控制,具有实际应用价值。

To solve the problems such as the driving redundancy due to the quantity of rope larger than the degree of freedom the difficulty in obtaining analytical solution caused by highly non-linear in the inverse kinematics process that the length of the rope solves joint angle and the large error of numerical calculation results in the presence of measurement interference,a 2-DOF rope driven parallel platform prototype is designed,and the kinematics model of the mechanism is built.Based on fuzzy decision,an anti-interference algorithm for the inverse kinematic calculation of the rope drive parallel mechanism is designed,which blurs the driving space and joint space and calculates the joint angle from the length of the rope,thereby suppressing the sensitivity of the over-constrained calculation with measurement noise.The numerical simulation technology is used to compare the designed algorithm with the traditional Newton iterative algorithm.The results show the fuzzy inverse kinematic algorithm has high caculation accuracy and stability,and practical value with its application of the motion control of rope-driven parallel mechanism.