화학공학소재연구정보센터
Korean Journal of Chemical Engineering, Vol.33, No.11, 3079-3084, November, 2016
Extremum seeking control using a partial sum of input-output product
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Recent extremum seeking control that uses a continuous perturbation and the integral feedback of perturbation-output product is based on a static nonlinear process. The method can be applied to dynamic nonlinear processes for tracking and maintaining the optimal operating points. It has several tuning parameters, such as the integral controller gain and the magnitude and frequency of the continuous perturbation signal. The frequency of the continuous perturbation signal should be low enough to ensure the time-scale separation between the real-time optimization and the process dynamics for the closed-loop stability. However, for some processes, fast perturbations are preferred because they can be attenuated easily in subsequent processes such as buffers and storages. For this, we propose an extremum seeking control method where the partial sum of perturbation-output product is used for a faster squarewave perturbation. Simulations for two processes of parallel competing reactions have been given, and a simple liquid level system to test extremum seeking control methods is suggested.
  1. Seborg DE, Edgar TF, Mellichamp DA, Doyle FJ, Process dynamics and control, 3rd Ed., Wiley, New York, U.S.A. (2010).
  2. Skogestad S, J. Process Control, 10(5), 487 (2000)
  3. Zhang CL, Ordonez R, Automatica, 45(3), 634 (2009)
  4. Khong SZ, Nesic D, Manzie C, Tan Y, Automatica, 49(7), 1970 (2013)
  5. Lee KS, Lee WK, AIChE J., 31, 667 (1985)
  6. Nesic D, Mohammadi A, Manzie C, IEEE Trans. Autom. Control, 58(2), 435 (2013)
  7. Korovin SK, Utkin VI, Automatica, 10, 525 (1974)
  8. Fu LN, Ozguner U, Automatica, 47(12), 2595 (2011)
  9. Krstic M, Wang HH, Automatica, 36(4), 595 (2000)
  10. Tan Y, Nesic D, Mareels IMY, Astolfi A, Automatica, 45(1), 245 (2009)
  11. Tan Y, Moase WH, Manzie C, Nesic D, Mareels IM, Proc. 29th Chinese Control Conference, July 29-31, Beijing, China (2010).
  12. Krstic M, Systems Control Letters, 39, 313 (2000)
  13. Tan Y, Nesic D, Mareels I, Automatica, 44(5), 1446 (2008)
  14. Scheinker A, Krstic M, Systems Control Letters, 63, 25 (2014)
  15. Dochain D, Perrier M, Guay M, Mathematics Computers in Simulation, 82, 369 (2011)
  16. Guay M, J. Process Control, 24(3), 98 (2014)
  17. Kim DH, Park DR, Lee J, Int. J. Hydrog. Energy, 38(11), 4429 (2013)
  18. Lee HC, Kim S, Heo JP, Kim DH, Lee J, ADCHEM 2015, Whistler, Canada (2015).
  19. Lee J, Edgar TF, Korean J. Chem. Eng., 33(2), 416 (2016)
  20. Bequette BW, Process dynamics modeling, analysis, and simulation, Prentice Hall, New Jersey, U.S.A. (1998).
  21. Lee J, Kim DH, Yang DR, Cho W, AIChE Spring Meeting, Austin, Texas, U.S.A. (2015).