改进粒子群算法的双电机转速同步控制
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摘要
为解决双电机同步控制系统在启动和有负载扰动时两电机产生同步误差的问题,提出了一种新的转速同步控制方法。在同步控制策略中引入交叉耦合控制的思想,对两电机的速度环采用不同数值的耦合参数分别进行补偿,以保证两电机的转速同步精度;采用粒子群算法对同步控制系统耦合参数进行选取,并且在粒子群算法中增加动态惯性权重和粒子变异来增强算法的寻优速度与精度;通过仿真及dSPACE实验显示了所提同步控制方法增强了系统的转速同步性和跟踪性,取得了优异的同步控制效果。
In order to solve the problem of synchronization error between two motors when starting and disturbing with load, a new speed synchronization control method is proposed. The idea of cross-coupling control is introduced in the synchronous control strategy, and the speed loops of two motors are compensated with different coupling parameters to ensure the speed synchronization accuracy of the two motors. Particle swarm optimization(PSO) is used to select coupling parameters of synchronous control system and dynamic inertia weight and particle mutation are added to PSO to enhance the speed and precision of the algorithm. Simulation and dSPACE experiments show that the proposed synchronization control method enhances the speed synchronization and tracking of the system and achieves excellent synchronization control effect.
In order to solve the problem of synchronization error between two motors when starting and disturbing with load, a new speed synchronization control method is proposed. The idea of cross-coupling control is introduced in the synchronous control strategy, and the speed loops of two motors are compensated with different coupling parameters to ensure the speed synchronization accuracy of the two motors. Particle swarm optimization(PSO) is used to select coupling parameters of synchronous control system and dynamic inertia weight and particle mutation are added to PSO to enhance the speed and precision of the algorithm. Simulation and dSPACE experiments show that the proposed synchronization control method enhances the speed synchronization and tracking of the system and achieves excellent synchronization control effect.
引文
[1] 高恒路,桑勇,邵龙潭.同步控制策略及其典型应用的研究[J].液压气动与密封,2012,32(5):1-7.
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[5] 韩仁银,郭阳宽,祝连庆,等.多电机同步控制综述[J].电机与控制应用,2017,44(6):8-12.
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[8] 夏长亮,李莉,谷鑫,等.双永磁电机系统转速同步控制[J].电工技术学报,2017,32(23):1-8.
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[10] Kennedy J,Eberhart R.Particle Swarm Optimization[J].Proc.of 1995 IEEE Int.Conf.Neural Networks,(Perth,Australia),2011,4(8):1942-1948.
[2] Tan L N.Analysis and Experimental Research on Synchronous Control Technology of CNC Machine Tool of Double Motor[J].Machine Tool & Hydraulics,2016,44(24):146-150.
[3] O'Dwyer A.Handbook of PI and PID Controller Tuning Rules[J].Automatica,2006,41(2):355-356.
[4] 王莉娜,朱鸿悦,杨宗军.永磁同步电动机调速系统PI控制器参数整定方法[J].电工技术学报,2014,29(5):104-117.
[5] 韩仁银,郭阳宽,祝连庆,等.多电机同步控制综述[J].电机与控制应用,2017,44(6):8-12.
[6] 崔皆凡,刘艳,闫红,等.基于模糊控制的多电机神经元PID同步控制[J].组合机床与自动化加工技术,2013(2):81-83.
[7] 王建红,陈耀忠,陈桂,等.基于交叉耦合控制的双电机同步控制系统研究[J].南京理工大学学报(自然科学版),2017,41(6):693-697.
[8] 夏长亮,李莉,谷鑫,等.双永磁电机系统转速同步控制[J].电工技术学报,2017,32(23):1-8.
[9] Awouda A E A,Bin Mamat R.New PID Tuning Rule Using ITAE Criteria[J].International Journal of Engineering,2010,3(6):171-176.
[10] Kennedy J,Eberhart R.Particle Swarm Optimization[J].Proc.of 1995 IEEE Int.Conf.Neural Networks,(Perth,Australia),2011,4(8):1942-1948.