Integration of Artificial Neural Networks and Linear Systems for the Output Feedback Control of Nonlinear Vibration Systems

摘要：

　　This paper analyzes the integration of neural networks and linear systems for the identification,state estimation and output feedback control of weakly nonlinear systems.Considering previous knowledge about the system given by approximated linear state-space models,linear observers and linear controllers,training algorithms for the neuro-identification,state neuro-estimation and output feedback neuro-control were derived considering the dynamics of the nonlinear system.It was found that the integrated linear-neuro model can identify the dynamics of the system much more accurately than a purely linear model or a purely neuro model.It was also found that the state estimation and vibration isolation performance of the system with integrated linear-neuro output feedback control is better than the system with linear control or neuro-control.

关键词： Artificial Neural Networks Linear Systems Control Theory Neuro-Control

作者: Javier G.Rázuri Antonio M.Cardenas Rahim Rahmani David Sundgren Ikuo Mizuuchi

作者单位: DSV Department,Stockholm University EED Department,Pontifical Catholic University of Perú MSE Department,Tokyo University of Agriculture and Technology

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 1850-1855

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）