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伺服系统的神经网络摩擦力自适应补偿研究 被引量:3

Study of the Friction Compensation in Servo Systems
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摘要 在高精度伺服系统中,摩擦力是影响其低速性能的关键因素。本文分析了摩擦力的特征、数学模型、及其对伺服系统性能的影响,提出了基于RBF网络的自适应摩擦力补偿方法,并将其与参数线化模型相比较。在某单轴速率/位置转台的控制系统中的应用结果表明,该方法能有效地改善伺服系统的性能。 In order to achieve high precision position/velocity control,friction must be appropriately compensated for.In this paper,the friction models,its impact on the servo system are analyzed,and the disadvantages of typical compensation methods are discussed firstly.Then,an adaptive friction compensation method using the RBF network is put forwarded.This compensation method is compared with the model identification method by applying them to the control of a oneaxis velocity/position simulator.It turns out that the RBF network can greatly improved the system tracking performance.
作者 张媚 李秀娟
出处 《计算技术与自动化》 2002年第4期11-15,33,共6页 Computing Technology and Automation
关键词 伺服系统 神经网络 摩擦力 自适应补偿 数学模型 参数化 servo systems RBF networks friction compensation
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参考文献10

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同被引文献22

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