Abstract
This paper proposes a recursive least squares algorithm for a distributed parameter system with missing observations. By using the finite difference method, the distributed parameter system can be turned into a lumped parameter system. Then a missing output identification model based recursive least squares algorithm is derived to estimate the unknown parameters of the lumped parameter system. Furthermore, the parameters of the distributed parameter system can be computed by the estimated parameters of the lumped parameter system. The simulation results indicate that the proposed method is effective.
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Recommended by Associate Editor Yongping Pan under the direction of Editor Duk-Sun Shim. This work is supported by the National Natural Science Foundation of China (Nos. 61403165,61374126), the Natural Science Foundation of Jiangsu Province (No. BK20131109), the Natural Science Foundation of Shandong Province (ZR2013FM021), the Post Doctoral Foundation of Jiangsu Province (No. 1501015A) and the Natural Science Fund for Colleges and Universities in Jiangsu Province (No. 16KJB120006).
Jing Chen received his B.Sc. degree in School of Mathematical Science and M.Sc. degree in School of Information Engineering from Yangzhou University (Yanghzou, China), in 2003 and 2006, respectively, and received his Ph.D. degree in the School of Internet of Things Engineering, Jiangnan University (Wuxi, China) in 2013. He is currently an associate professor in College of Science, Jiangnan University (Wuxi, China). His research interests include Processing Control and system identification.
Bin Jiang received the Ph.D. degree in Automatic Control from Northeastern University (Shenyang, China) in 1995. He had ever been postdoctoral fellow, research fellow, invited professor and visiting professor in Singapore, France, USA and Canada, respectively. Now he is a Chair Professor of Cheung Kong Scholar Program in Ministry of Education and Dean of College of Automation Engineering in Nanjing University of Aeronautics and Astronautics (Nanjing, China). He currently serves as Associate Editor or Editorial Board Member for a number of journals such as IEEE Trans. On Control Systems Technology; IEEE Trans. On Fuzzy Systems; Int. J. Of Control, Automation and Systems; Nonlinear Analysis: Hybrid Systems, etc. He is a senior member of IEEE, Chair of Control Systems Chapter in IEEE Nanjing Section, a member of IFAC Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. His research interests include intelligent fault diagnosis and fault tolerant control and their applications.
Juan Li received her B.Sc degree in School of Automation Engineering from Shandong University (Jinan, China) in 1994, an M.Sc. degree in School of Electrical Engineering and Information Engineering from Lanzhou Polytechnic University (Lan-zhou, China) in 2000, and a Ph.D. degree in School of Information Science and Engineering from Ocean University of China (Qingdao, China) in 2008. She was a Visiting Professor in School of Automation, Tsinghua University (Beijing, China) from 2010 to 2011 and in the Department of Chemical and Material Engineering, University of Alberta (Edmonton, Canada) from 2015 to 2016, respectively. Her current research interests include fault diagnosis and fault-tolerant control and intelligent detection and control.
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Chen, J., Jiang, B. & Li, J. Missing Output Identification Model Based Recursive Least Squares Algorithm for a Distributed Parameter System. Int. J. Control Autom. Syst. 16, 150–157 (2018). https://doi.org/10.1007/s12555-016-0606-5
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DOI: https://doi.org/10.1007/s12555-016-0606-5