Smith predictor with sliding mode control for processes with large dead times

Mehta, Utkal; Kaya, İbrahim

doi:10.1515/jee-2017-0081

Abstract

The paper discusses the Smith Predictor scheme with Sliding Mode Controller (SP-SMC) for processes with large dead times. This technique gives improved load-disturbance rejection with optimum input control signal variations. A power rate reaching law is incorporated in the sporadic part of sliding mode control such that the overall performance recovers meaningfully. The proposed scheme obtains parameter values by satisfying a new performance index which is based on biobjective constraint. In simulation study, the efficiency of the method is evaluated for robustness and transient performance over reported techniques.

References

[1] A. O’Dwyer Handbook of PI and PID controller tuning rules, 3rd ed. UK: Imperial College Press, 2009.10.1142/p575
Search in Google Scholar Back to article
[2] O. Smith, “A controller to overcome dead time”, ISA J, vol. 6, p.2833, 1959.
Search in Google Scholar Back to article
[3] M. R. Matausek and A. D. Micic, “A modified smith predictor for controlling a process with an integrator and long dead-time”, IEEE Trans. Automatic Contr., vol. 41, no.8, pp. 1199 - 1203, 1996.
Search in Google Scholar Back to article
[4] S. Majhi and D. Atherton, “Obtaining controller parameters for a new smith predictor using auto tuning”, Automatica, vol. 36, pp. 1651-8, 2000.
Search in Google Scholar Back to article
[5] I. Kaya, “IMC based automatic tuning method for PID controllers a smith predictor configuration”, Computers & Chemical Engineering, vol. 28, pp. 281-290, 2004.10.1016/j.compchemeng.2003.01.001
Search in Google Scholar Back to article
[6] A. S. Rao, V. Rao and M. Chidambaram, “Set point weighted modified smith predictor for integrating and double integrating processes with time delay”, ISA Transactions, vol. 46, no.1, 2007.10.1016/j.isatra.2006.05.00217240376
Search in Google Scholar Back to article
[7] A. S. Rao and M. Chidambaram, “Analytical design of modified smith predictor a twodegrees-of-freedom control scheme for second order unstable processes with time delay”, ISA Transactions, vol. 47, pp. 407-419, 2008.10.1016/j.isatra.2008.06.00518706559
Search in Google Scholar Back to article
[8] A. S. Rao, S. Seethaladevi, S. Uma and M. Chidambaram, “Enhancing the performance of parallel cascade control using Smith predictor”, ISA Trans., vol. 48, pp. 220-227, 2009.10.1016/j.isatra.2008.10.01119054509
Search in Google Scholar Back to article
[9] M. R. Matauseka and A. I. Ribic, “Control of stable, integrating and unstable processes by the modified smith predictor”, Journal of Process Control, vol. 22, pp. 338-343, 2012.10.1016/j.jprocont.2011.08.006
Open DOI Search in Google Scholar Back to article
[10] M. Ajmeri and A. Ali, “Two degree of freedom control scheme for unstable processes with small time delay”, ISA Transactions, vol. 56, pp. 308-326, 2015.10.1016/j.isatra.2014.12.00725617941
Search in Google Scholar Back to article
[11] V. F. Kuzishchin, E. I. Merzlikina and V. Hoang, “Study of the control system with the smith predictor and autotuning algorithm AT-2 for thermal control objects with the constant speed actuator”, MATEC Web of Conferences, vol. 91, 2017, pp. 010-018.10.1051/matecconf/20179101018
Search in Google Scholar Back to article
[12] I. S. Jesus and R. S. Barbosa, Lecture Notes Electrical Engineering Springer, Cham, 2016, ch. Smith Predictor Tuned Through Fuzzy Fractional PID Controller, pp. 71-80.10.1007/978-3-319-43671-5_7
Search in Google Scholar Back to article
[13] C. Rodrguez, J. Normey-Rico, J. Guzmn, M. and Berenguel, “On the filtered smith predictor with feedforward compensation”, Journal of Process Control, vol. 41, pp. 35-46, 2016.10.1016/j.jprocont.2016.02.005
Open DOI Search in Google Scholar Back to article
[14] V. I. Utkin, “Variable structure system with sliding mode”, IEEE Trans. Automatic Contr., vol. 22, no.2, pp. 212-221, 1997.10.1109/TAC.1977.1101446
Search in Google Scholar Back to article
[15] W. Perruquetti and J. P. Barbot, Sliding mode control Engineering, Automation and Control Series, Marcel Dekker Inc., New York (USA), 2002.10.1201/9780203910856
Search in Google Scholar Back to article
[16] B. Bandyopadhyay, F. Deepak and K.-S. Kim, SlidingMode Control Using Novel Sliding Surfaces, B.Media, Ed. Springer Science, 2009.10.1007/978-3-642-03448-0
Search in Google Scholar Back to article
[17] O. Camacho and R. Rojas, “A general slidingmode controller for nonlinear chemical processes”, J. Dyn. Syst. Meas. Control, vol. 122, pp. 650 - 655, 2000.10.1115/1.1318351
Search in Google Scholar Back to article
[18] O. Camacho and F. D. la Cruz, “Smith predictor based-sliding mode controller for integrating processes with elevated deadtime”, ISA Transactions, vol. 43, pp. 257 - 270, 2004.10.1016/S0019-0578(07)60035-4
Open DOI Search in Google Scholar Back to article
[19] R. Rojas, O. Camacho and L. Gonzalez, “A sliding mode control proposal for open-loop unstable processes”, ISA Tran., vol. 43, pp. 243 - 255, 2004.10.1016/S0019-0578(07)60034-2
Search in Google Scholar Back to article
[20] O. Camacho, R. Rojas and W. Gabin, “Some long time delay sliding mode control approaches”, ISA Transactions, vol. 46, pp. 95-101, 2007.10.1016/j.isatra.2006.06.00217241631
Open DOI Search in Google Scholar Back to article
[21] S. Sivaramakrishnan, A. K. Tangirala and M. Chidambaram, “Sliding mode controller for unstable systems”, Chem. Biochem. Eng. Q., vol. 22, no.1, pp. 41 - 47, 2008.
Search in Google Scholar Back to article
[22] U. Mehta and R. Rojas, “Smith predictor based sliding mode control for a class of unstable processes”, Transactions of the Institute of Measurement and Control, vol. 39, no.5, pp. 706-714, 2017.10.1177/0142331215619973
Search in Google Scholar Back to article
[23] J. J. Slotine and W. Li, Applied Nolinear Control, N. Englewood Cliffs, Ed. Prentice-Hall, 1991.
Search in Google Scholar Back to article
[24] J. Y. Hung, W. Gao and J. C. Hung, “Variable structure control: A survey”, IEEE Trans. Ind. Electr., vol. 40, no.1, pp. 2 - 22, 1993.10.1109/41.184817
Search in Google Scholar Back to article
[25] O. Garpinger, Hägglund, K. J. Åström, “Performance and robustness trade-offs PID control”, Journal of Process Control, vol. 24, no.5, pp. 568-577, 2014.10.1016/j.jprocont.2014.02.020
Open DOI Search in Google Scholar Back to article
[26] D. Shi, J. Wang and L. Ma, “Design of balanced proportional-integral-derivative controllers based on bilevel optimisation”, IET Control Theory and Applications, vol. 5, no.1, pp. 84-92, 2011.10.1049/iet-cta.2009.0561
Search in Google Scholar Back to article
[27] L. Sun, D. Li and K. Lee, “Optimal disturbance rejection for PI controller with constraints on relative delay margin”, ISA Transactions, vol. 63, pp. 103-111, 2016.10.1016/j.isatra.2016.03.01427038886
Search in Google Scholar Back to article
[28] X. S. Yang Nature-inspired metaheuristical gorithms, United Kingdom:Luniver Press, 2011.
Search in Google Scholar Back to article
[29] J. Kennedy and R. Eberhart, “Particle swarm optimization”, Proc. IEEE Int. Conf. Neural Networks, vol. 4, Perth, Australia, 1995, pp. 1942-1948.10.1109/ICNN.1995.488968
Open DOI Search in Google Scholar Back to article
[30] R. Poli, J. Kennedy and T. Blackwell, “Particle swarm optimization. an overview”, Springer, Swarm Intelligence, vol. 1, pp. 35-57, 2007.10.1007/s11721-007-0002-0
Search in Google Scholar Back to article

Smith predictor with sliding mode control for processes with large dead times

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