Extreme learning machine-based stable adaptive control for a class of nonlinear system

摘要：

　　Extreme Learning Machine(ELM),recently developed by Huang et al.,has been demonstrating an exciting learning algorithm for Single hidden Layer Feedback Neural Networks(SLFN).In this paper,the ELM has been introduced to approximate the unknown functions,which may not be parameterized and so make it impossible to develop an adaptive controller.Besides,the Nussbaum-type gain method is also incorporated into the controller design to counteract the unknown coefficient of the control section.It is proved that the proposed approach is able to ensure boundedness of all the signals in the closed-loop system,and the state variables converge to zero asymptotically.

关键词： Extreme learning machine adaptive control nonlinear system

作者: Haisen Ke Wenrui Li

作者单位: College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 387-391

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）