3-P(4S)并联机构分析与多目标性能优化

Mechanism Analysis and Multi-target Performance Optimization of 3-P(4S) Parallel Mechanism

针对3-P(4S)并联平台,首先对其进行了位置反解,提出了由BP神经网络和拟Newton法相结合的混合数值法,并以此对机构进行了位置正解,求解精度可达到10-8数量级,求解时间在20 ms内。然后通过对位置解求导可得到机构动平台和分支杆件的速度和加速度。根据运动学分析的结果,应用牛顿欧拉方法构建该机构的动力学模型,并对机构的数值算例进行了动力学仿真验证。最后综合考虑机构的动力学性能、刚度性能和速度性能,分别推导了其评价指标,并应用改进的加权求和法对该机构进行多目标的尺寸优化。通过多目标的尺寸优化,该机构的动力学性能和速度性能提升了2倍,刚度性能提升了3倍。

The object was to solve the dynamics analysis and multi-target performance optimization of 3 -P（4S） parallel mechanism. Firstly, inverse kinematics of 3 -P（4S） parallel mechanism was solved, and hybrid numerical algorithm was proposed, which was composed of BP neural network and quasi- Newton method algorithm. The algorithm could solve the forward kinematics of 3 - P （4S） parallel mechanism in less than 20 ms by three step iterations, and the accuracy was on the level of 10^-8, which can realize the high accuracy and real-time control of 3 -P（4S） parallel mechanism. Then the velocity and acceleration of the moving platform and limbs were obtained by the derivative of the position solution. According to the results of kinematic analysis, the dynamic model of the mechanism was constructed by Newton Euler method, and the dynamic simulation of the numerical example was utilized to verify the dynamic model of 3 - P （4S） parallel mechanism. From the verification results, both of the two were exactly the same. Finally, considering the dynamic performance, stiffness performance and speed performance of the 3 - P（4S） parallel mechanism, an improved genetic algorithm was utilized to optimize the 3- P（4S） parallel mechanism. Through the muhi-objective performance optimization, the dynamic performance and speed performance of the mechanism were improved by two times, and the stiffness performance was increased by three times.