Robust Output Feedback Control for A Class of Nonlinear Systems by Adaptive Neural Networks

摘要：

By Nussbaum-type gain technique and adaptive neural network, a robust adaptive neural network controller is established for a class of uncertain nonlinear systems. Under this controller, the output is regulated to a neighborhood of origin by appropriately choosing design parameters, and all signals of the closed-loop are kept bounded. The feasibility is investigated by an illustrative simulation example.

关键词： Radial Basis Function Neural Network Output Feedback Backstepping

作者: LONG Lijun XIE Chengkang

作者单位: School of Mathematics and System Science,Southwest University

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 4995-5000

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）