Multiple model approach to linear parameter varying time-delay system identification with em algorithm

Journal of the Franklin Institute

Volumn 351, Issue 12, 2014, Pages 5565-5581

  Yang, Xianqiang ^a   Gao, Huijun ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DELAY CONTROL SYSTEMS; DISTILLATION COLUMNS; MAXIMUM PRINCIPLE; TIME DELAY; TIMING CIRCUITS;

CONSTANT TIME DELAYS; EXPECTATION-MAXIMIZATION ALGORITHMS; HIGH PURITY DISTILLATION COLUMNS; IDENTIFICATION PROBLEM; INDUSTRIAL PROCESSS; IRRIGATION CHANNELS; LINEAR PARAMETER VARYING; MULTIPLE-MODEL APPROACHES;

PARAMETER ESTIMATION;

EID: 84911360071     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2014.09.015     Document Type: Article

References (31)

1. C. Onat A new concept on PI design for time delay systems: weighted geometrical center Int. J. Innov. Comput. I. 9 4 2013 1539 1556
2. M.T. Alrifai, M. Zribi, M. Rayan, and M.S. Mahmoud On the control of time delay power systems Int. J. Innov. Comput. I. 9 2 2013 769 792
3. S. Yin, H. Luo, and S. Ding Real-time implementation of fault-tolerant control systems with performance optimization IEEE Trans. Ind. Electron. 61 5 2014 2402 2411
4. S. Yin, S. Ding, A. Haghani, and P. Zhang A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee eastman process J. Process Control 22 9 2012 1567 1581
5. W. Sun, H. Gao, and B. Yao Adaptive robust vibration control of full-car active suspensions with electro-hydraulic actuators IEEE Trans. Control Syst. Technol. 21 6 2013 2417 2422
6. J. Shamma, and M. Athans Guaranteed properties of gain scheduled control for linear parameter-varying plants Automatica 27 3 1991 559 564
7. V. Laurain, M. Gilson, R. Toth, and H. Garnier Refined instrumental variable methods for identification of lpv box-Jenkins models Automatica 46 6 2010 959 967
8. X. Jin, B. Huang, and D. Shook Multiple model lpv approach to nonlinear process identification with em algorithm J. Process Control 21 1 2011 182 193
9. Y. Zhao, B. Huang, H. Su, and J. Chu Prediction error method for identification of lpv models Control Eng. Pract. 22 1 2012 180 193
10. Z. Xu, J. Zhao, J. Qian, and Y. Zhu Nonlinear mpc using identified lpv model Ind. Eng. Chem. Res. 48 6 2009 3043 3051
11. R. Toth, Modeling and identification of linear parameter-varying systems: an orthonormal basis function approach (Ph.D. thesis), Delft University of Technology, 2008.
12. A. Venkat, P. Vijaysai, and R. Gudi Identification of complex nonlinear processes based on fuzzy decomposition of the steady state space J. Process Control 13 6 2003 473 488
13. Y. Zhu, Z. Xu, A method of lpv model identification for control, in: Proceedings of the 17th World Congress, Seoul, Koera, 2008.
14. A. Dempster, N. Laird, and D. Rubin Maximum likelihood from incomplete data via the em algorithm J. R. Stat. Soc. 39 1 1977 1 38
15. J. Richard Time-delay systems an overview of some recent advances and open problems Automatica 39 2003 1667 1694
16. X. Su, L. Wu, P. Shi, and Y.-D. Song H ∞model reduction of t-s fuzzy stochastic systems IEEE Trans. Syst., Man, Cybern. - Part B: Cybern. 42 6 2012 1574 1585
17. X. Su, P. Shi, L. Wu, M. Basin, Reliable filtering with strict dissipativity for t-s fuzzy time-delay systems, IEEE Trans. Cybern., http://dx.doi.org/10.1109/TCYB.2014.2308983.
18. J. Qiu, G. Feng, and J. Yang Improved delay-dependent h-infinity filtering design for discrete-time polytopic linear delay systems IEEE Trans. Circuits Syst.-II 55 2 2008 178 182
19. J. Qiu, G. Feng, and J. Yang A new design of delay-dependent robust h-infinity filtering for discrete-time t-s fuzzy systems with time-varying delay IEEE Trans. Fuzzy Syst. 17 5 2009 1044 1058
20. T. Simao, Multiple model identification in systems with variable dynamics (Masters thesis), Lisboa, Portugal, 2011.
21. M. Hansen, J. Stoustrup, J. Bendtsen, An lpv model for a marine cooling system with transport delays, in: The 14th International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation, Wien, Austria, 2012.
22. Y. Bolea, V. Puig, and J. Blesa Linear parameter varying modeling and identification for real-time control of open-flow irrigation canals Environ. Model. Softw. 53 2014 87 97
23. G. Mercere, H. Palsson, and T. Poinot Continuous-time linear parameter-varying identification of a cross flow heat exchanger a local approach IEEE Trans. Control Syst. Technol. 19 1 2011 64 76
24. J. Morningred, B. Seborg, D. Seborg, and D. Mellichamp An adaptive nonlinear predictive controller Chem. Eng. Sci. 47 4 1992 755 762
25. L. Ljung System Identification: Theory for the User 1999 PTR Prentice Hall Upper Saddle River, NJ
26. G.J. McLachlan, and T. Krishnan The EM Algorithm and Extensions (2nd Edition) 2007 John Wiley & Sons Hoboken New Jersey
27. X. Litrico, and V. Fromion Simplified modeling of irrigation canals for controller design J. Irrig. Drain. Eng. 130 5 2004 373 383
28. S.K. Ooi, M. Krutzen, and E. Weyer On physical and data driven modelling of irrigation channels Control Eng. Pract. 13 2005 461 471
29. J. Huang, G. Ji, Y. Zhu, and P. van den Bosch Identification of multi-model lpv models with two scheduling variables J. Process Control 22 2012 1198 1208
30. S. Skogestad Dynamics and control of distillation columns - a tutorial introduction Chem. Eng. Res. Des. 75 1997 539 562
31. L. Chen, A. Tulsyan, B. Huang, and F. Liu Multiple model approach to nonlinear system identification with an uncertain scheduling variable using em algorithm J. Process Control 23 10 2013 1480 1496