基于6-UCU型平台并联机床的轨迹时间优化

Trajectory Time Optimization Based on 6-UCU Platform Parallel Machine Tool

本文针对基于6-UCU型Stewart平台的并联机床提出了一种轨迹时间优化方法。建立该运动平台的运动学逆解模型。通过三次多项式插值对上平台的轨迹点进行插值,通过反解模型求出各个驱动臂对应的位移。建立时间优化的模型,使用遗传算法结合五次多项式插值对轨迹点之间的速度,加速度进行求解。计算得出优化后的运行时间与未优化前对比优化了14.9%。最后将得到的加速度导入到ADMAS模型中进行仿真验证,结果表明该轨迹运行平稳,仿真测量的驱动臂位移与计算得出无明显差别。

This paper proposes a trajectory time optimization method for parallel machine tools based on the 6-UCU Stewart platform.In this paper,the inverse kinematics model of the motion platform was established firstly.The trajectory points of the upper platform are interpolated by cubic polynomial interpolation,and the corresponding displacement of each driving arm is obtained by the inverse solution model.Establish a time-optimized model and use genetic algorithm combined with fifth-degree polynomial interpolation to solve the velocity and acceleration between trajectory points.It is calculated that the optimized running time is optimized by 14.9%compared with that before the optimization.Finally,the obtained acceleration was imported into the ADMAS model for simulation verification.The results show that the trajectory runs smoothly,and the measured displacement of the driving arm is not significantly different from the calculation.