Data filtering and auxiliary model based recursive least squares estimation algorithm for OEMA systems

摘要：

Based on the filtering theory and the auxiliary model identification idea, we present a filtering and auxiliary model based recursive least squares identification algorithm for an output-error moving average system. The proposed algorithm has a higher computational efficiency compared with the auxiliary model based recursive extended least squares algorithm.

关键词： Recursive identification parameter estimation least squares auxiliary model filtering output-error moving average (OEMA) systems

作者: Dongqing Wang Shouqing Sun Feng Ding Guiling Song

作者单位: Automation Engineering, Qingdao University, Qingdao 266071, and with the Lanyan Group Ltd. as a post Hismile College, Qingdao 266100, China School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China Lanyan Group Ltd, Zibo 255300, China

会议类型: 国际会议

会议名称: 2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)

会议地点: 杭州

会议语种:英文

页码: 477-481

在线出版日期: 2011-05-01（万方平台首次上网日期，不代表论文的发表时间）