Robust dynamic surface control of flexible joint robots using recurrent neural networks

作     者：Zhiqiang MIAO Yaonan WANG 

作者机构：College of Electrical and Information Engineering Hunan University 

出 版 物：《控制理论与应用（英文版）》 (Journal of Control Theory and Applications)

年 卷 期：2013年第11卷第2期

页      面：222-229页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supported by the National Natural Science Foundation of China(Nos.60835004,61175075) the Hunan Provincial Innovation Foundation for Postgraduate(No.CX2012B147) 

主　　题：Dynamic surface control Flexible joint robots Robust H-infinity control Recurrent neural network 

摘      要：A robust neuro-adaptive controller for uncertain flexible joint robots is presented. This control scheme integrates H^infinity disturbance attenuation design and recurrent neural network adaptive control technique into the dy- namic surface control framework. Two recurrent neural networks are used to adaptively learn the uncertain functions in a flexible joint robot. Then, the effects of approximation error and filter error on the tracking performance are attenuated to a prescribed level by the embedded H-infinity controller, so that the desired H-infinity tracking performance can be achieved. Finally. simulation results verifv the effectiveness of the nronosed control scheme.