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Auto-Tuning PID Based on Extremum Seeking Algorithm for an Industrial Application

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AETA 2019 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application (AETA 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 685))

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Abstract

The PID controller implementation on the industry is an active area of study, however, according to the technique used is possible not having optimal and good performance due to the difficulties in the process identification and parameter tuning of the system since there is no full information of the industrial process. In last years PID auto-tuning methodologies have been developed which let synthesize efficient polynomial controllers because the parameters, generally, are optimal in some sense. In this paper is showed a PID auto-tuning through Extremum Seeking algorithm (ES) in a flow control plant implemented with blocks programming in a programmable logic controller (PLC), this block system acquires input signals obtained by the plant sensors, in this case, a flow sensor, consequently a control signal is sent to the variable frequency drive of the pump system, the objective control is to maintain the flow constantly through the system in the desired reference. In the following section the block diagram of the controlled system is presented, the auto-tuning ES algorithm, the simulation results, and the real-time implementation on the industrial process, finally, some conclusions and final implementation comment considering some future work is developed.

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References

  1. Duque-Marín, A., Lopez, J.A., Navas, A.F.: Auto-tuning of a PID controller implemented in a PLC using swarm intelligence. Prospectiva 15(1), 35–41 (2017)

    Article  Google Scholar 

  2. Killingsworth, N.J., Krstic, M.: PID tuning using extremum seeking: online, model-free performance optimization. IEEE Control Syst. Mag. 26(1), 70–79 (2006)

    Article  MathSciNet  Google Scholar 

  3. Yu, C.C.: Autotuning of PID Controllers: A Relay Feedback Approach. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  4. Gade, S.S., Shendage, S.B., Uplane, M.D.: On line auto tuning of PID controller using successive approximation method. In: 2010 International Conference on Recent Trends in Information, Telecommunication and Computing, pp. 277–280, March 2010

    Google Scholar 

  5. Seidi Khorramabadi, S., Bakhshai, A.: Critic-based self-tuning PI structure for active and reactive power control of VSCs in microgrid systems. IEEE Trans. Smart Grid 6(1), 92–103 (2015)

    Article  Google Scholar 

  6. Bevrani, H., Habibi, F., Babahajyani, P., Watanabe, M., Mitani, Y.: Intelligent frequency control in an AC microgrid: online PSO-based fuzzy tuning approach. IEEE Trans. Smart Grid 3(4), 1935–1944 (2012)

    Article  Google Scholar 

  7. Hjalmarsson, H., Gevers, M., Gunnarsson, S., Lequin, O.: Iterative feedback tuning: theory and applications. IEEE Control Syst. Mag. 18(4), 26–41 (1998)

    Article  Google Scholar 

  8. Dochain, D., Perrier, M., Guay, M.: Extremum seeking control and its application to process and reaction systems: a survey. Math. Comput. Simul. 82(3), 369–380 (2011). 6th Vienna International Conference on Mathematical Modelling

    Google Scholar 

  9. Brunton, S.L., Kutz, J.N.: Data-driven Science and Engineering: Machine Learning, Dynamical Systems, and Control. Cambridge University Press, Cambridge (2019)

    Book  Google Scholar 

  10. ANITCO: Manual de Operación y Mantenimiento Unidad de Mantenimiento en Automatización (UEA), April 2015

    Google Scholar 

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Acknowledgment

This paper is part of project number 111077657914 and contract number 031-2018, funded by the Colombian Administrative Department of Science, Technology, and Innovation (COLCIENCIAS) and developed by the ICE3 Research Group at Universidad Tecnologica de Pereira (UTP) and CALPOSALLE Group at Universidad de La Salle.

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Correspondence to M. Bueno-López .

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Arias-Patiño, A., Zapata-Lombana, A., Salazar-Caceres, F., Bueno-López, M. (2021). Auto-Tuning PID Based on Extremum Seeking Algorithm for an Industrial Application. In: Cortes Tobar, D., Hoang Duy, V., Trong Dao, T. (eds) AETA 2019 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2019. Lecture Notes in Electrical Engineering, vol 685. Springer, Cham. https://doi.org/10.1007/978-3-030-53021-1_24

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