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On line diagnostics and self-tuning method for the fluidized bed temperature controller

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents the method of on-line diagnostics of the bed temperature controller for the fluidized bed boiler. Proposed solution is based on the methods of statistical process control. Detected decrease of the bed temperature control quality is used to activate the controller self-tuning procedure. The algorithm that provides optimal tuning of the bed temperature controller is also proposed. The results of experimental verification of the presented method is attached. Experimental studies were carried out using the 2 MW bubbling fluidized bed boiler.
Rocznik
Strony
31--46
Opis fizyczny
Bibliogr. 17 poz., rys., tab., wz.
Twórcy
autor
  • Cracow University of Technology, Institute of Thermal Engineering and Air Quality Protection, Warszawska 24, 31-155 Cracow, Poland
Bibliografia
  • [1] Aygun H., Demirel H.: Comparison of PSO-PID, FLC and PID in a circulating fluidized bed boiler. In: Proc. 7th Int. Conf. on Electrical and Electronics Engineering (2011), 376–380.
  • [2] Basu P.: Combustion and Gasification in Fluidized Bed. CRC Press, Boca Raton 2006.
  • [3] Budnik M., StanekW., Rusinowski H.: Application of neural model ling in hybrid control model of fluidized bed boiler fired with coal and biomass. In: Proc. 13th Int. Carpathian Control Conf. (2012), 69–74.
  • [4] Chien I.-L.: IMC-PID control ler design – An extension. In: Proc. IFAC Adaptive Control of Chemical Processes Conf. (1988), 147–152.
  • [5] Fu P., Yu X.-N., Wang H.: Research on fuzzy control algorithm for bed temperature control of circulating fluidized bed boiler. In: Proc. Fourth Int. Conf. Machine Learning and Cybernetics (2005), 825–828.
  • [6] Hou G., Zhang Y., Zhang J.: Real-coding genetic algorithm-based model identification for bed temperature of 300 MW CFB boiler. Chinese Control and Decision Conf. (2011), 2019–2025.
  • [7] Johnson M.A., Moradi M.H.: PID New Identification and Design Methods. Springer-Verlag, London 2005.
  • [8] Liu X., Wang Sh., Xing L.: Fuzzy self-tuning PID temperature control for biomass pyrolysis fluidized bed combustor. In: Proc. 2nd IEEE Int. Conf. on Information Management and Engineering (2010), 384–387.
  • [9] Liu Ch.-Y., Wang J., Li Q., Song X.-L., Song Z.-Y.: The study of the control of the bed temperature in the circulating fluidized bed boiler based on the fuzzy control system. In: Proc. Int. Conf. on Computer and Communication Technologies in Agriculture Engineering (2010), 285–288.
  • [10] Liukkonen M., Halikka E., Hiltunen T., Hiltunen Y.: Adaptive soft sensor for fluidized bed quality: Applications to combustion of biomass. Fuel Process. Technol. 105(2013), 46–51.
  • [11] Lixia B., Junxia Z., Song F.: Modeling and simulating of bed temperature control of circulating fluidized boiler. J. North China Electric Power Univ. 30(2003), 1, 53–56.
  • [12] Oakland J.S.: Statistical Process Control. Butterworth-Heinemann, Bodmin 2003.
  • [13] O’Dwyer A.: Handbook of PI and PID Control ler Tuning Rules. Imperial College Press, London 2006.
  • [14] Porzuczek J.: Optimization of the fluidized bed boilers operation in nonstationary states. Monograph 405, Environmental Engineering Ser., Cracow University of Technology, Krakow 2012 (in Polish).
  • [15] Porzuczek J.: Dynamic model identification of the low-power fluidized bed boiler. Czasopismo Techniczne, 4-Ś/2012 (2012), 157–170 (in Polish).
  • [16] Porzuczek J.: Transfer matrix model of the bubbling fluidized bed boiler. Arch. Thermodyn. 32(2011), 3, 245–26.
  • [17] www.metsoautomation.com (acessed on 01.03.2016).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cde9a331-1e7e-4885-827b-503ef988375d
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