针对机电耦合系统的改进自适应跳跃粒子群算法动态优化方法

Yan Sun, Weiguo Zhao, Qiang Li, Jianxin Wu
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引用次数: 0

摘要

机电耦合系统的动态优化是一个多学科的力学理论问题。研究了这类问题的优化问题。介绍了粒子群算法。为了解决这一不足,提出了一种新的自适应跳跃粒子群优化算法(ALPSO),并对其收敛性进行了分析。最后,利用蚁群算法对机床主轴系统机电耦合重构进行优化。应用实例表明,该方法能在有限的时间内得到实际的优化参数,是解决此类问题的一种有效途径。
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Improved adaptive leap particle swarm algorithm dynamic optimization method against electromechanical coupling system
Dynamic optimization of electromechanical coupling system is a multi-subject problem on mechanics theory. The optimization of such kind problem is studied. Particle swarm optimization (PSO) is introduced. In order to resolve the insufficiency, a new kind of adaptive leap particle swarm optimization (ALPSO) is presented and the astringency analysis is finished. Finally, ALPSO is used to optimize electromechanical coupling reshape machine tool principal axis system. The results of application example proved that practical optimization parameters can be obtained in limited time by the method, and it is a kind of effective way to solve such kind of problem.
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