伺服系统的神经网络摩擦力自适应补偿研究被引量：1

Study of the Friction Compensation in Servo Systems

下载PDF

导出

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。文章分析了摩擦力的特性、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,并将其与参数线性化模型相比较。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. 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 one-axis velocity/position simulator. It turns out that the RBF network can greatly improved the system tracking performance.

作者李秀娟张媚

机构地区南京航空航天大学

出处《电气传动》北大核心 2003年第6期28-31,共4页 Electric Drive

关键词伺服系统神经网络摩擦力自适应补偿数学模型 servo systems RBF networks friction compensation

分类号 TM921.541 [电气工程—电力电子与电力传动] TP183 [自动化与计算机技术—控制理论与控制工程]

引文网络
相关文献

参考文献10

1[1]Atherton. Nonlinear Control Engineering-describing Function Analysis and Design. Van Nostrand Reinhold, London. 1975
2[2]BO L C, Pavelesou D. The Friction-speed Relation and Its Influence on the Critical Velocity of the Stick-slip Motion.Wear, 1982,3: 277～289
3[3]Armstrong B. Friction: Experimental Determination, Modelling and Compensation. IEEE Int. Conf. On Robotics and Automation, Philadelphia, 1988,3:1422～ 1427
4[4]Dupont P E, Armstrong B, Canudas dde Wit C. A Survey of Analysis Tools and Compensation Methods for Control of Machines with Friction. Automatica, 1994, 30 (7): 1083 ～1138
5[5]Canudas de Wit C, Olsson H, Astrom K J et al. New Model for Control of Systems with Friction IEEE Trans. Automatic Control, 1995,40(3): 419～ 425
6[6]Canudas de Wit C, Noel P, Aubin A et al. Adaptive Friction Compensation in Robot Manipulators: low velocities,Int. J.Robotics System,1991,10(3) :189～199
7[7]Canudas de Wit C, Astrom K J, Braun K. Adaptive Friction Compansation in DC-motor Drives, IEEE J. Robot and Automation, 1987,3 (6) :681～689
8[8]Canudas de Wit C, Ge S S. Adaptive Friction Compensation for Systems with generalized Velocity/Position Friction Dependency. In Proc. IEEE Conf. Decision and Control,SanDiego, Dec. 1997,3:2465～2470
9[9]Kim Y H, Lewis F L. Reinforced Adaptive Learning Neural Network Based Friction Compansation for High Speed and Precision, In Proc. IEEE Conf. Decision and Control Dec,1998:1064～1069
10黄进,叶尚辉.基于CMAC网络的摩擦补偿研究[J].中国机械工程,1999,10(3):269-272. 被引量：7