NONLINEAR BAYESIAN STATE ESTIMATION: REVIEW AND RECENT TRENDS

摘要：

Process monitoring and control requires estimation of quality variables, which are often not measurable directly. A cost effective approach to monitor these variables in real time is to employ model based soft sensing and state estimation techniques. Dynamic model based state estimation is a rich and highly active area of research and many novel approaches have emerged over last few years. In this paper, we review recent developments in the area of recursive nonlinear Bayesian state and parameter estimation techniques.

关键词： Soft Sensing Bayesian State Estimation Nonlinear Observers Multi-rate Systems Fault Diagnosis.

作者: J. Prakash R.B. Gopaluni Sachin C. Patwardhan Shankar Narasimhan Sirish L. Shah

作者单位: Madras Institute of Technology Campus, Anna University, Chennai, 600044, India University of British Columbia, Canada Indian Institute of Technology Bombay, Powai, Mumbai 400076, India Indian Institute of Technology Madras, Chennai 600036, India University of Alberta, Edmonton, T6G 2G6 Canada

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: 450-455

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）