Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

doi:10.1016/j.cjche.2014.09.028

›› 2014, Vol. 22 ›› Issue (11/12): 1268-1273.DOI: 10.1016/j.cjche.2014.09.028

• 过程系统工程与过程安全 • 上一篇下一篇

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

Hongwei Wang, Tao Liu

School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China

收稿日期:2014-01-08 修回日期:2014-03-14 出版日期:2014-12-28 发布日期:2014-12-24
通讯作者: Tao Liu
基金资助:
Supported in part by the National Thousand Talents Program of China, the National Natural Science Foundation of China (61473054), and the Fundamental Research Funds for the Central Universities of China.

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

Hongwei Wang, Tao Liu

School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China

Received:2014-01-08 Revised:2014-03-14 Online:2014-12-28 Published:2014-12-24
Supported by:
Supported in part by the National Thousand Talents Program of China, the National Natural Science Foundation of China (61473054), and the Fundamental Research Funds for the Central Universities of China.

摘要/Abstract

摘要： In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of statemeasurement, an identification algorithm based on the singular value decomposition (SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method.

关键词: Non-uniformly sampling system, State-space model identification, Singular value decomposition, Recursive algorithm

Abstract: In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of statemeasurement, an identification algorithm based on the singular value decomposition (SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method.

Key words: Non-uniformly sampling system, State-space model identification, Singular value decomposition, Recursive algorithm

Hongwei Wang, Tao Liu . Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition[J]. , 2014, 22(11/12): 1268-1273.

参考文献

[1] D. Li, S.L. Shah, T. Chen, Identification of fast-rate models from multirate data, Int. J. Control. 74 (2) (2001) 680-689.
[2] D. Li, S.L. Shah, T. Chen, K.Z. Qi, Application of dual-rate modeling to CCR octane quality inferential control, IEEE Trans. Control Syst. Technol. 11 (1) (2003) 43-51.
[3] R.D. Gudi, S.L. Shah, M.R. Gray, Multirate state and parameter estimation in an antibiotic fermentation with delayed measurements, Biotechnol. Bioeng. 44 (11) (1994) 1271-1278.
[4] F. Ding, T. Chen, Combined parameter and output estimation of dual-rate systems using an auxiliary model, Automatica 40 (10) (2004) 1739-1748.
[5] F. Ding, T. Chen, Adaptive digital control of Hammerstein nonlinear systems with limited output sampling, SIAM J. Control. Optim. 45 (6) (2006) 2257-2276.
[6] M. Embirucu, C. Fontes, Multirate multivariable generalized predictive control and its application to a slurry reactor for ethylene polymerization, Chem. Eng. Sci. 61 (17) (2006) 5754-5767.
[7] T. Liu, F.R. Gao, Industrial Process Identification and Control Design: Step-test and Relay-experiment-based Methods, Springer Press, London UK, 2012.
[8] W.H. Li, S.L. Shah, D.Y. Xiao, Kalman filters in non-uniformly sampled multirate systems: for FDI and beyond, Automatica 44 (1) (2008) 199-208.
[9] F. Ding, T. Chen, Hierarchical identification of lifted state-space models for general dual-rate systems, IEEE Trans. Circ. Syst. I Regul. Pap. 52 (6) (2005) 1179-1187.
[10] Y.J. Liu, L. Xie, F. Ding, An auxiliary model based recursive least squares parameter estimation algorithm for nonuniformly sampled multirate systems, Proc. Inst. Mech. Eng. Part I -J. Syst. Control Eng. 223 (4) (2009) 445-454.
[11] H. Raghavan, A.K. Tangirala, R.B. Gopaluni, S.L. Shah, Identification of chemical process with irregular output sampling, Control. Eng. Pract. 14 (5) (2006) 467-480.
[12] F. Ding, L. Qiu, T. Chen, Reconstruction of continuous time systems from their non-uniformly sampled discrete time systems, Automatica 45 (2) (2009) 324-332.
[13] J.L.Wang, L.Q. Zhao, T. Yu, On-line estimation of batch feeding fermentation process using state-space model and insensitive Kalman filtering, Chin. J. Chem. Eng. 18 (2) (2010) 258-264.
[14] E.K. Larsson, M. S. Derstro, Identification of continuous time AR processes from unevenly sampled data, Automatica 38 (4) (2002) 709-718.
[15] E.K. Larsson, M. Mossberg, M. S. Derstro, Identification of continuous-time ARX models from irregularly sampled data, IEEE Trans. Autom. Control 52 (3) (2007) 417-427.
[16] R. Sanchis, P. Albertos, Recursive identification under scarce measurementsconvergence analysis, Automatica 38 (3) (2002) 909-918.
[17] Y. Zhu, H. Telkamp, J.H.Wang, Q.L. Fu, Systemidentification using slow and irregular output samples, J. Process Control 19 (1) (2009) 58-67.
[18] T. Liu, C. Shao, An extended closed-loop subspace identificationmethod for error-invariables systems, Chin. J. Chem. Eng. 20 (6) (2012) 1136-1141.
[19] H. Tamura, T. Yoshikawa, Large-scale Systems Control and Decision Making, Marcal Dekker Press, New York, 1990.
[20] F. Ding, Adaptive Control and System Identification, Tsinghua University Press, Beijing, 2002.
[21] H. Tanizaki, Nonlinear Filter: Estimation and Application, Springer Press, New York, 1996.

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价