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磁悬浮精密隔振器结构设计及控制算法研究

Research on Structure Design and Control Algorithm of Maglev Precise Isolator
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摘要 针对半主动隔振器存在精度不高、频带较窄等问题,设计了一种由永磁铁和电磁铁组成的混合磁悬浮隔振器结构,建立了动力学数学模型。根据控制精度和要求,提出一种改进型的双闭环控制策略,即采用改进型遗传算法对外环的自抗扰控制器(ADRC)参数进行优化,采用模糊神经网络对内环的PID控制器参数进行实时整定。通过MATLAB仿真比较,结果表明,采用优化控制算法后,系统超调量将小于1%,隔振器各参数稳定时间缩短了1.5 s左右。可见,改进后的控制算法具有较快的收敛速度,从而使混合磁悬浮隔振器具有更好的隔振性能。 Aiming at the problems of lower precision and narrower frequency band width with the semi-active vibration isolator,a kind of hybrid maglev isolator is designed,which are composed of permanent magnets and electromagnets,and the dynamic model is discussed. An improved double closed loop control strategy is proposed according to the control precision and control requirements. In the strategy,the active disturbance rejection control(ADRC) controller parameters are optimized by improved genetic algorithm,and the proportion integration differentiation( PID) controller parameters are determined via fuzzy neural network. The simulation results in MATLAB show that overshoot of the system is less than 1% after the optimal control algorithm,and the stability time of the system is shorter 1. 5 s than that of the system using the traditional control strategy. Obviously,the improved control algorithm has a faster convergence speed,which makes the hybrid magnetic suspension isolator has better vibration isolation performance.
出处 《机械科学与技术》 CSCD 北大核心 2018年第3期443-450,共8页 Mechanical Science and Technology for Aerospace Engineering
基金 江苏省自然科学基金项目(BK20161192) 江苏省数字化制造技术重点实验室开放课题项目(HJDML-1001)资助
关键词 磁悬浮隔振器 改进型遗传算法 模糊神经网络 双闭环控制 MATLAB maglev isolator improved genetic algorithm fuzzy neural network double-closed loop MATLAB
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