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双马达伺服系统改进PSO和ECF相结合同步控制 被引量:1

Synchronization control of dual motor servo system with improved PSO and ECF
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摘要 为了提高数控转台双马达伺服系统同步控制精度,设计了一种改进粒子群优化(PSO)算法和误差修正反馈(ECF)控制方案,可达到更高同步控制精度并提升运动性能。研究结果表明:在系统中输入阶跃信号后再对其瞬态响应性能进行测试,通过系统响应性能的各项评价指标,利用改进后的复合控制方法可以显著降低系统超调幅度并获得更小稳态误差,经过优化同步控制获得不超过±0.05°的踪误差。经过共反馈同步误差校正并引入改进粒子群算法后,使系统超调显著减小并大幅降低了波动性,最终优化了系统控制性能。该研究的双马达伺服系统提高了同步控制精度,可以灵活地拓展到同类型领域,具有很好的实际价值。 In order to improve the synchronous control accuracy of CNC turntable dual motor servo system,an improved particle swarm optimization(PSO) algorithm and error correct feed-back(ECF)control scheme were designed,which can achieve higher synchronization control precision and improve motion performance.The results show that the transient response performance tested after the step signal is input into the system.According to the evaluation indexes of system response performance,the improved composite control method can significantly reduce the overshoot amplitude of system and obtain smaller steady-state error.The tracking error is less than ±0.05°after optimized synchronous control.After the common feedback synchronization error correction and the introduction of improved particle swarm optimization algorithm,the overshoot of system is significantly reduced and the fluctuation is greatly reduced,and finally the control performance of system is optimized.The dual-motor servo system improves the synchronous control precision and can be flexibly extended to the same field,which has a good practical value.
作者 王飞飞 张明 王强 WANG Feifei;ZHANG Ming;WANG Qiang(Intelligent Manufacturing College,Xinxiang Vocational and Technical College,Xinxiang 453000,Henan,China;College of Mechanical Engineering,Henan Polytechnic University,Zhengzhou 451460,Henan,China;Design Department,Luoyang Huaguan Gear Co.,Ltd.,Luoyang 471131,Henan,China)
出处 《中国工程机械学报》 北大核心 2022年第2期151-155,共5页 Chinese Journal of Construction Machinery
基金 国家自然科学基金资助项目(51905496)。
关键词 双马达系统 同步控制 反馈同步误差 改进粒子群优化(PSO)算法 dual motor system synchronous control feed back synchronization error improved particle swarm optimization(PSO)algorithm
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