Iterative identification of output error model for industrial processes with time delay subject to colored noise

doi:10.1016/j.cjche.2015.08.021

Chin.J.Chem.Eng. ›› 2015, Vol. 23 ›› Issue (12): 2005-2012.DOI: 10.1016/j.cjche.2015.08.021

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Iterative identification of output error model for industrial processes with time delay subject to colored noise

Shijian Dong¹, Tao Liu¹, Mingzhong Li², Yi Cao³

1 Institute of Advanced Control Technology, Dalian University of Technology, Dalian 116024, China;
2 Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, UK;
3 School of Energy, Environment and Agrifood, Cranfield University, Cranfield MK43 0AL, UK

Received:2015-05-22 Revised:2015-07-17 Online:2016-01-19 Published:2015-12-28
Contact: Tao Liu
Supported by:
Supported 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.

Iterative identification of output error model for industrial processes with time delay subject to colored noise

Shijian Dong¹, Tao Liu¹, Mingzhong Li², Yi Cao³

1 Institute of Advanced Control Technology, Dalian University of Technology, Dalian 116024, China;
2 Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, UK;
3 School of Energy, Environment and Agrifood, Cranfield University, Cranfield MK43 0AL, UK

通讯作者: Tao Liu
基金资助:
Supported 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.

Abstract

Abstract: To dealwith colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares (ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.

Key words: Time delay system, Output error model, Recursive least-squares, Instrumental variable, Variable forgetting factor

摘要： To dealwith colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares (ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.

关键词: Time delay system, Output error model, Recursive least-squares, Instrumental variable, Variable forgetting factor

Shijian Dong, Tao Liu, Mingzhong Li, Yi Cao. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. Chin.J.Chem.Eng., 2015, 23(12): 2005-2012.

Shijian Dong, Tao Liu, Mingzhong Li, Yi Cao. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. Chinese Journal of Chemical Engineering, 2015, 23(12): 2005-2012.

References

[1] L. Ljung, Perspectives on system identification, Annu. Rev. Control. 34 (1) (2010) 1-12.

[2] T. Liu, F.R. Gao, Industrial process identification and control design: Step-test and relay-experiment-based methods, Springer, London, UK, 2012.

[3] T. Liu, Q.G. Wang, H.P. Huang, A tutorial review on process identification from step or relay feedback test, J. Process Control 23 (10) (2013) 1597-1623.

[4] J.P. Richard, Time-delay systems: An overview of some recent advances and open problems, Automatica 39 (10) (2003) 1667-1694.

[5] B. Zhou, Z.Y. Li, W.X. Zheng, G.R. Duan, Stabilization of some linear systems with both state and input delays, Syst. Control Lett. 61 (10) (2012) 989-998.

[6] O. Xu, Y. Fu, H. Su, L. Li, A selectivemoving windowpartial least squares method and its application in process modeling, Chin. J. Chem. Eng. 22 (5) (2014) 799-804.

[7] H. Wang, T. Liu, Recursive state-space model identification of non-uniformly sampled systems using singular value decomposition, Chin. J. Chem. Eng. 22 (12) (2014) 1268-1273.

[8] Y.Y. Du, J.S.H. Tsai, H. Patil, L.S. Shieh, Y. Chen, Indirect identification of continuoustime delay systems from step responses, Appl. Math. Model. 35 (2) (2011) 594-611.

[9] T. Liu, F.R. Gao, A generalized relay identification method for time delay and nonminimum phase processes, Automatica 45 (4) (2009) 1072-1079.

[10] O. Gomez, Y. Orlov, I.V. Kolmanovsky, Online identification of SISO linear timeinvariant delay systems from output measurements, Automatica 43 (12) (2007) 2060-2069.

[11] P.J. Gawthrop, M.T. Nihtila, A.B. Rad, Recursive parameter estimation of continuous systems with unknown time delay, Control Theory Adv. Technol. 5 (3) (1980) 227-248.

[12] A.B. Rad, W.L. Lo, K.M. Tsang, Simultaneous on line identification of rational dynamics and time delay: A correlation based approach, IEEE Trans. Control Syst. Technol. 11 (6) (2003) 957-959.

[13] X.M. Ren, A.B. Rad, P.T. Chan, W.L. Lo, Online identification of continuous-time systems with unknown time delay, IEEE Trans. Autom. Control 50 (9) (2005) 1418-1422.

[14] J. Na, X.M. Ren, Y.Q. Xia, Adaptive parameter identification of linear SISO systems with unknown time-delay, Syst. Control Lett. 66 (2014) 43-50.

[15] G. Ferretti, C.Maffezzoni, R. Scattolini, Recursive estimation of time delay in sampled systems, Automatica 27 (4) (1991) 653-661.

[16] A. Elnaggar, G.A. Dumont, A.L. Elshafei, New method for delay estimation, Proceedings of the 29th IEEE conference on decision and control, 3 1990, pp. 1929-1930.

[17] S. Bedoui, M. Ltaief, K. Abderrahim, Online identification of multivariable discrete time delay systems using a recursive least square algorithm, Math. Probl. Eng. (2013) 1-18.

[18] S. Bedoui, M. Ltaief, K. Abderrahim, A new generalized vector observation for discrete-time delay systems identification, European control conference 2013, pp. 1922-1927.

[19] S. Bedoui, M. Ltaief, K. Abderrahim, New results on discrete-time delay systems identification, Int. J. Autom. Comput. 9 (6) (2012) 570-577.

[20] T. Söderström, P. Stoica, System identification, Prentice Hall, New York, USA, 1989.

[21] L. Ljung, System identification: Theory for the user, Second ed. Prentice-Hall, Englewood Cliffs, New Jersey, 1999.

[22] T. Söderström, P. Stoica, Instrumental variable methods for system identification, Circ. Syst. Signal Process. 21 (1) (2002) 1-9.

[23] T. Söderström, P. Stoica, Comparison of some instrumental variable methods-Consistency and accuracy aspects, Automatic 17 (1) (1981) 101-115.

[24] F. Ding, T.W. Chen, Parameter estimation for dual-rate systems with finite measurement date, dynamics of continuous, Discret. Impulsive Syst. Ser. B Appl. Algorithm 11 (1) (2004) 101-121.

[25] D.S. Bernstein, Matrix mathematics: Theory, facts and formulas, Princeton University Press, 2009.

Iterative identification of output error model for industrial processes with time delay subject to colored noise

Iterative identification of output error model for industrial processes with time delay subject to colored noise

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