基于嵌套粒子群算法的平面机构尺度综合与构型优选

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Particle swarm optimization（PSO） is used to study the dimensional synthesis and optimal type selection of planar mechanisms. A nested PSO method is proposed, which can search the dimension parameters with main PSO and search the pose parameters with sub PSO. The method is applied to the study of path generation problem by building the dimensional synthesis model and optimal type selection model with the nested PSO algorithm. The validity and universality of the method are verified by two case studies, which are dimensional synthesis of planar four bar linkages and optimal type selection of planar multi-bar mechanisms. The main advantage of this method lies on the capability to produce multiple optimized solutions, which provides broader selection for the designer. With nested PSO method, the problem of dimensional synthesis, pose optimization and optimal type selection of planar mechanisms can be solved in a unified approach.将粒子群算法应用于平面机构尺度综合与构型优选的研究。以轨迹生成问题为研究案例,提出一种嵌套粒子群算法,利用粒子总群进行机构尺度参数的搜索,利用粒子子群进行机架位姿参数的搜索,利用不同构型粒子群优化目标函数的对比,建立机构的尺度综合与构型优选模型。通过平面四杆机构的尺度综合实例和平面多杆机构的构型优选实例,验证该方法的有效性与通用性。该方法的主要优点：对同一优化目标能够产生多组不同的优化解,从而给设计者提供更大的选择空间;应用同一算法能够同时解决平面机构的尺度综合、机架位姿优化和构型优选问题。