Robust Asymptotic Tracking of Uncertain Nonlinear Systems Using Artificial Neural Networks

摘要：

The problem of robust asymptotic tracking for uncertain nonlinear systems is considered in this paper. The controlled systems considered in this paper are more general than the strict feedback form nonlinear systems. The robust tracking controller is designed based on Backstepping approach with the uncertain terms being accounted for Artificial Neural Networks (ANN). The weights of ANN are updated on-line with adaptive algorithm to be designed. All signals in the closed-loop systems are bounded and the tracking error convergent to zero asymptotically through the proposed controller.

作者: Ying Zhou Qiang Zang

作者单位: College of Automation Nanjing University of Posts and Telecommunications Nanjing, Republic of China, School of Automation Southeast University Nanjing, Republic of China,210096

会议类型: 国际会议

会议名称: Fourth International Conference on Impulsive and Hybrid Dynamical Systems(ICIHDS 2007)(第四届国际脉冲和混合动力系统学术会议)

会议地点: 南宁

会议语种:英文

在线出版日期: 2007-07-20（万方平台首次上网日期，不代表论文的发表时间）