某新型电液伺服系统神经网络自抗扰控制
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摘要
针对某新型同源平衡及定位电液伺服系统,设计了一种基于RBF神经网络在线整定ESO参数的神经网络自抗扰控制器(NNADRC)。利用RBF神经网络在线整定可调误差校正增益,实现非线性特性的实时、精确估计和补偿。数值仿真结果表明,NNADRC控制的稳态精度明显高于ADRC控制,且对外部负载扰动和内部参数摄动具有良好的鲁棒性,可以实现电液伺服系统的快速、平稳、高精度、无超调稳定控制。
Aiming at simultaneous balancing and positioning of the electro-hydraulic servo( EHS) system,a novel neural network based active disturbance rejection control( NNADRC) strategy is developed. In the NNADRC,the radial basis function( RBF) neural network is employed in on-line updating parameters of the extended state observer( ESO). By on-line updating the estimator gains of the ESO,the real time and accurate estimation and compensation can be made for the nonlinear behavior and external disturbance of the system. The effectiveness and efficiency of the system are critically investigated by numerical simulations. The results show that compared with the conventional ADRC strategy,its stability and robustness are better and its accuracy is higher.It is of fast,stable,smooth and accurate control function.
Aiming at simultaneous balancing and positioning of the electro-hydraulic servo( EHS) system,a novel neural network based active disturbance rejection control( NNADRC) strategy is developed. In the NNADRC,the radial basis function( RBF) neural network is employed in on-line updating parameters of the extended state observer( ESO). By on-line updating the estimator gains of the ESO,the real time and accurate estimation and compensation can be made for the nonlinear behavior and external disturbance of the system. The effectiveness and efficiency of the system are critically investigated by numerical simulations. The results show that compared with the conventional ADRC strategy,its stability and robustness are better and its accuracy is higher.It is of fast,stable,smooth and accurate control function.
引文
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[8]齐晓慧,李杰,韩帅涛.基于BP神经网络的自适应自抗扰控制及仿真[J].兵工学报,2013,34(6):776-782.
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[10]周振雄,曲永印,杨建东,等.一种改进型ADRC实现的机床进给用永磁直线同步电动机调速系统[J].中国机械工程,2008,19(21):2561-2565.
[11]周振雄,杨建东,曲永印,等.基于自抗扰控制器的磁浮平台水平推力控制[J].机械工程学报,2008,44(9):193-199.
[12]周振雄,曲永印,杨建东,等.采用改进型自抗扰控制器的平面磁轴承悬浮控制[J].电工技术学报,2010,25(6):31-38.
[2]韩京清.从PID技术到“自抗扰控制”技术[J].控制工程,2002,9(3):13-18.
[3]Han J Q. From PID to Active Disturbance Rejection Control[J].IEEE Transactions on Industrial Electronics,2009,56(3):900-906.
[4]陈文英,褚福磊,阎绍泽.基于自适应遗传算法分步优化设计智能桁架结构自抗扰振动控制器[J].机械工程学报,2010,46(7):74-81.
[5]任海鹏,朱峰.基于免疫克隆选择算法的无刷直流电动机速度自抗扰控制器优化设计[J].电机与控制学报,2010,14(9):69-74.
[6]刘星桥,唐琳,朱丽婷.模糊自抗扰控制的三电机同步协调协调[J].电机与控制学报,2013,17(4):104-109.
[7]乔国林,童朝南,孙一康.基于神经网络自抗扰控制的结晶器液位拉速协调系统研究[J].自动化学报,2007,33(6):641-648.
[8]齐晓慧,李杰,韩帅涛.基于BP神经网络的自适应自抗扰控制及仿真[J].兵工学报,2013,34(6):776-782.
[9]李匡成.基于RBF神经网络的伺服系统自适应自抗扰控制[J].电气自动化,2010,32(2):23-25.
[10]周振雄,曲永印,杨建东,等.一种改进型ADRC实现的机床进给用永磁直线同步电动机调速系统[J].中国机械工程,2008,19(21):2561-2565.
[11]周振雄,杨建东,曲永印,等.基于自抗扰控制器的磁浮平台水平推力控制[J].机械工程学报,2008,44(9):193-199.
[12]周振雄,曲永印,杨建东,等.采用改进型自抗扰控制器的平面磁轴承悬浮控制[J].电工技术学报,2010,25(6):31-38.