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机械手的神经网络自适应滑动模控制器设计
引用本文:孙富春,孙增圻,尔联结. 机械手的神经网络自适应滑动模控制器设计[J]. 航空学报, 1997, 18(2): 168-172
作者姓名:孙富春  孙增圻  尔联结
作者单位:清华大学计算机科学与技术系,北京航空航天大学自动控制系
摘    要: 针对多关节机械手的鲁棒跟随控制器设计问题,提出了一种新的机械手神经网络自适应滑动模控制器设计方法,机械手的动力学非线性假设是完全未知的。在提出的控制结构中,高斯径向基函数神经网络用于在线补偿机械手的动力学非线性,参数学习律由稳定性理论得到。给出了系统稳定性和参数收敛性的证明。最后提出方法的可行性通过仿真得到验证。

关 键 词:机械手  自适应  滑动模控制  神经网络  

DESIGN OF ADAPTIVE SLIDING MODE CONTROLLER FOR MANIPULATORS USING NEURAL NETWORKS
Sun Fuchun,Sun Zengqi. DESIGN OF ADAPTIVE SLIDING MODE CONTROLLER FOR MANIPULATORS USING NEURAL NETWORKS[J]. Acta Aeronautica et Astronautica Sinica, 1997, 18(2): 168-172
Authors:Sun Fuchun  Sun Zengqi
Affiliation:1. Department of Computer Science and Technology, National Laboratory of Intelligence Technology and Systems, Tsinghua University, Beijing 100084;2. Dept. of Automatic Control, Beijing University of Aeronautics and Astr onautics, Beijing, 100083
Abstract:A new adaptive sliding mode controller using neural networks is proposed for the robust tracking controller design of an n link manipulator with unknown dynamics nonlinearities. The controller employs Gaussian radial basis function(RBF) neural networks to adaptively compensate for the plant nonlinearities. The system stability and tracking error convergence are proved using stability theory that yields a stable parameter learning law. Finally, the effectiveness of the proposed control approach is illustrated through simulation studies.
Keywords:manipulators   adaptiveness   sliding mode control   neural networks  
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