| 基于气动装置神经网络模型的anti-windup控制器设计 |
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| 引用本文： | 宋强,刘芳,任伟.基于气动装置神经网络模型的anti-windup控制器设计[J].东南大学学报(自然科学版),2006(Z1). |
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| 作者姓名： | 宋强 刘芳 任伟 |
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| 作者单位： | 杭州电子科技大学电子信息学院 Power Research Laboratory McMaster University Hamilton L8S 4K1 Ontario Canada |
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| 摘 要： | 为提高气动系统的控制效果,以Levenberg-Marquardt算法训练多层前馈神经网络,建立了一气动装置的神经网络模型并推导出ARX模型.基于气动装置的ARX模型,采用Ragazzini方法设计了anti-windup控制器.实时控制结果表明,所设计的控制器有效地克服了控制死区和阀的饱和效应,实现了对该气动装置快速和高精度的控制.
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| 关 键 词： | 气动装置 anti-windup 神经网络 Levenberg-Marquardt算法 Ragazzini方法 |
Anti-windup controller design based on neural network model of pneumatic actuator |
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| Song Qiang Liu Fang Ren Wei.Anti-windup controller design based on neural network model of pneumatic actuator[J].Journal of Southeast University(Natural Science Edition),2006(Z1). |
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| Authors: | Song Qiang Liu Fang Ren Wei |
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| Institution: | Song Qiang1 Liu Fang2 Ren Wei1 |
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| Abstract: | In order to improve control performance of pneumatic systems,utilizing multilayered feedforward neural network trained with the Levenberg-Marquard method,a neural network model of a pneumatic actuator is established,from which an ARX(auto-regressive with exogenous input) model is derived.Based on the built ARX model,an anti-windup controller is designed by the Ragazzini method for the pneumatic actuator.The real-time control result demonstrates that with this controller the dead-zone and valve saturation of the pneumatic actuator can be overcome efficiently,and accurate position control with fast response speed is obtained. |
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| Keywords: | pneumatic actuator neural network anti-windup Levenberg-Marquardt method Ragazzini method |
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