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Design, Simulation and Comparison of Controllers for Temperature Profile Tracking Control of a Heat Flow System

Year 2020, Volume: 13 Issue: 2, 828 - 838, 31.08.2020
https://doi.org/10.18185/erzifbed.766645

Abstract

Bu makalede, ısı-akış sistemine uygulanan üç farklı kontrolcünün tasarımı, simülasyonu ve performans karşılaştırması sunulmuştur. İlk olarak, ısı-akış sisteminin dinamik modeli elde edilmiş ve devamında ısı kontrolünü gerçekleştirmek için kayan kipli kontrol (KKK), adaptif kayan kipli kontrol (AKKK) ve adaptif kesir dereceli kayan kipli kontrol (AKDKKK) yöntemleri tasarlanmış ve uygulanmıştır. Tasarlanan kontrolcülerin performansını analiz etmek için Matlab/Simulink programı aracılığıyla ısı–akış sisteminin simülasyonu oluşturulmuş ve tasarlanan kontrolcülerin performansı analiz edilmiştir. Simülasyon ortamından elde edilen referans sıcaklık takip hatası, adaptasyon kazancı, ani değişimlere karşı kontrolcünün tepkisi, maksimum aşım, yükselme ve yerleşme zamanı gibi sonuçlar sunulmuş ve elde edilen sonuçlardan AKDKKK’nün diğer kontrolcülere göre referans sıcaklığı daha az hata ile takip ettiği, daha düşük aşım, yükselme ve yerleşme zamanına sahip olduğu gözlemlenmiştir. Ayrıca, KKK uygulandığında en yüksek referans sıcaklık takip hatası, yükselme ve yerleşme zamanına sahip olduğu gözlemlenmiştir.

References

  • Agrawal, R. A., Pandelidis, I.O., & Pecht, M., (1987). “Injection-molding process control- A rewiev”, Polym. Eng. Sci., 27(18), 1345–1357. https://doi.org/10.1002/pen.760271802
  • Omatu, S., Yusof, R., Sinohara, K., & Hotta, M., (1992). “Temperature control for heating cylinder by multivariable STC”, Trans. Syst. Contr. Inform. Eng., 5(3), 102–110.
  • Seaman, M., Desrochers, A.-A., & List, G.-F., (1994). “Multiobjective optimization of a plastic injection molding process”, IEEE Trans. Contr. Syst. Technology, 2(3), 157–168. DOI: 10.1109/87.317974
  • Taur, J.-S., Tao, C.-W., & Tsai, C.-C., (1995). “Temperature control of a plastic extrusion barrel using PID fuzzy controllers”, Proceedings IEEE Conference on Industrial Automation and Control: Emerging Technology Applications. DOI: 10.1109/IACET.1995.527590
  • Lin, C.-T., Juang, C.-F., & Li, C.-P. (1999). “Temperature control with a neural fuzzy inference network”, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on. 29(3), 440-451. DOI: 10.1109/5326.777078
  • Petráš, I., & Vinagre, B.-M., (2002). “Practical application of digital fractional-order controller to temperature control”, Acta Montanistica Slovaca, 7(2), 131-13.
  • Juang, C.-F., & Chen, J.-S (2003). “A recurrent neural fuzzy network controller for a temperature control system”, The 12th IEEE International Conference on Fuzzy Systems, FUZZ'03, St Louis ,USA. DOI: 10.1109/FUZZ.2003.1209398
  • Ramos, H.-M.-S.-G., Assuncao, F., Ribeiro, A.-L., & Ramos, P.-M., (2004). “A low-cost temperature controlled system to test and characterize sensors”, 7th AFRICON Conference in Africa, Gaborone, Botswana. DOI: 10.1109/AFRICON.2004.1406715
  • Can, K., & Başçi, A., (2017). “Temperature Control of A Heat Flow Experimental Setup via Fractional-Order PI Controller”, 2nd International Conference on Advanced Engineering Technologies (ICADET 2017), Bayburt, Turkey.
  • Ahn, H.-Y. Bhambhani, V., & Chen, Y.-Q., (2008). “Fractional-order integral and derivative controller design for temperature profile control”, 2008 Chinese Control and Decision Conference, Shandong, China. DOI: 10.1109/CCDC.2008.4598234
  • Jain, M., Rani, A., Pachauri, N., Singh, V., & Mittal, A.-P., (2019). “Design of fractional order 2-DOF PI controller for real-time control of heat flow experiment”, Engineering Science and Technology, an International Journal, 22(1), 215-228. https://doi.org/10.1016/j.jestch.2018.07.002
  • Young, K.-D., Utkin, V.-I., & Özgüner, Ü, (1999). “A control engineer’s guide to sliding mode control”, IEEE Trans. Control Syst. Technol., 7(3), 328–342.
  • Ioannou, P., & Sun, J., (2012). “Robust adaptive control”, Courier Corporation.
  • Åströ, K.-J., & Wittenmark, W., (2013). “Adaptive control”, Courier Corporation.
  • Jaemin, B., Jin, M., & Han, S., (2016). “A new adaptive sliding-mode control scheme for application to robot manipulators”, IEEE Transactions on Industrial Electronics 63(6), 3628-3637. DOI: 10.1109/TIE.2016.2522386
  • Liao, Y.-W., Pan, S., Borrelli, F., & Hedrick, J.-K., (2018). “Adaptive sliding mode control without knowledge of uncertainty bounds”, 2018 Annual American Control Conference (ACC), Milwaukee, WI, USA. DOI:10.23919/ACC.2018.8431124
  • Heat Flow Experiment Setup https://www.quanser.com/products/heat-flow-experiment/ Gutman. S., (1979). “Uncertain Dynamical Systems: A Lyapunov Min-Max Approach”, IEEE Trans. Autom. Control, 24(3), 437–443. DOI: 10.1109/TAC.1979.1102073
  • Vinagre, B.-M. Podlubny, I., Hernandez, A., & Feliu, V. (2000). “Some approximations of fractional order operators used in control theory and applications”, Fractional Calculus and Applied Analysis, 3(3), 231-248.
  • Podlubny, I., (1999). “Fractional differential equations”, New York: Academic Press.
  • Zeinali, M., & A., Khajepour, (2010). “Height control in laser cladding using adaptive sliding mode technique: theory and experiment”, Journal of Manufacturing Science and Engineering, 132(4). https://doi.org/10.1115/1.4002023

Design, Simulation and Comparison of Controllers for Temperature Profile Tracking Control of a Heat Flow System

Year 2020, Volume: 13 Issue: 2, 828 - 838, 31.08.2020
https://doi.org/10.18185/erzifbed.766645

Abstract

In this paper, the design, simulation and performance comparison of the three different controllers applied to the heat flow system (HFS) are presented. First, the dynamic model of the HFS was obtained and so as to test the temperature control, sliding mode controller (SMC), adaptive sliding mode controller (ASMC) and adaptive fractional order sliding mode controller (AFOSMC) are designed and applied. To analyse the performance of the designed controllers a simulation environment is developed via the Matlab/Simulink software. The results, obtained through a simulation environment are represented by tracking error, adaptation gain, response to sudden changes, maximum overshoot, rise time and settling time and they showed that the heat flow system follows the reference temperature profile trajectory with less errors, overshoot, rise time and settling time by using the AFOSMC than the other controllers. Also, the maximum errors, rise time and settling time occurred when the sliding mode controller is used.

References

  • Agrawal, R. A., Pandelidis, I.O., & Pecht, M., (1987). “Injection-molding process control- A rewiev”, Polym. Eng. Sci., 27(18), 1345–1357. https://doi.org/10.1002/pen.760271802
  • Omatu, S., Yusof, R., Sinohara, K., & Hotta, M., (1992). “Temperature control for heating cylinder by multivariable STC”, Trans. Syst. Contr. Inform. Eng., 5(3), 102–110.
  • Seaman, M., Desrochers, A.-A., & List, G.-F., (1994). “Multiobjective optimization of a plastic injection molding process”, IEEE Trans. Contr. Syst. Technology, 2(3), 157–168. DOI: 10.1109/87.317974
  • Taur, J.-S., Tao, C.-W., & Tsai, C.-C., (1995). “Temperature control of a plastic extrusion barrel using PID fuzzy controllers”, Proceedings IEEE Conference on Industrial Automation and Control: Emerging Technology Applications. DOI: 10.1109/IACET.1995.527590
  • Lin, C.-T., Juang, C.-F., & Li, C.-P. (1999). “Temperature control with a neural fuzzy inference network”, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on. 29(3), 440-451. DOI: 10.1109/5326.777078
  • Petráš, I., & Vinagre, B.-M., (2002). “Practical application of digital fractional-order controller to temperature control”, Acta Montanistica Slovaca, 7(2), 131-13.
  • Juang, C.-F., & Chen, J.-S (2003). “A recurrent neural fuzzy network controller for a temperature control system”, The 12th IEEE International Conference on Fuzzy Systems, FUZZ'03, St Louis ,USA. DOI: 10.1109/FUZZ.2003.1209398
  • Ramos, H.-M.-S.-G., Assuncao, F., Ribeiro, A.-L., & Ramos, P.-M., (2004). “A low-cost temperature controlled system to test and characterize sensors”, 7th AFRICON Conference in Africa, Gaborone, Botswana. DOI: 10.1109/AFRICON.2004.1406715
  • Can, K., & Başçi, A., (2017). “Temperature Control of A Heat Flow Experimental Setup via Fractional-Order PI Controller”, 2nd International Conference on Advanced Engineering Technologies (ICADET 2017), Bayburt, Turkey.
  • Ahn, H.-Y. Bhambhani, V., & Chen, Y.-Q., (2008). “Fractional-order integral and derivative controller design for temperature profile control”, 2008 Chinese Control and Decision Conference, Shandong, China. DOI: 10.1109/CCDC.2008.4598234
  • Jain, M., Rani, A., Pachauri, N., Singh, V., & Mittal, A.-P., (2019). “Design of fractional order 2-DOF PI controller for real-time control of heat flow experiment”, Engineering Science and Technology, an International Journal, 22(1), 215-228. https://doi.org/10.1016/j.jestch.2018.07.002
  • Young, K.-D., Utkin, V.-I., & Özgüner, Ü, (1999). “A control engineer’s guide to sliding mode control”, IEEE Trans. Control Syst. Technol., 7(3), 328–342.
  • Ioannou, P., & Sun, J., (2012). “Robust adaptive control”, Courier Corporation.
  • Åströ, K.-J., & Wittenmark, W., (2013). “Adaptive control”, Courier Corporation.
  • Jaemin, B., Jin, M., & Han, S., (2016). “A new adaptive sliding-mode control scheme for application to robot manipulators”, IEEE Transactions on Industrial Electronics 63(6), 3628-3637. DOI: 10.1109/TIE.2016.2522386
  • Liao, Y.-W., Pan, S., Borrelli, F., & Hedrick, J.-K., (2018). “Adaptive sliding mode control without knowledge of uncertainty bounds”, 2018 Annual American Control Conference (ACC), Milwaukee, WI, USA. DOI:10.23919/ACC.2018.8431124
  • Heat Flow Experiment Setup https://www.quanser.com/products/heat-flow-experiment/ Gutman. S., (1979). “Uncertain Dynamical Systems: A Lyapunov Min-Max Approach”, IEEE Trans. Autom. Control, 24(3), 437–443. DOI: 10.1109/TAC.1979.1102073
  • Vinagre, B.-M. Podlubny, I., Hernandez, A., & Feliu, V. (2000). “Some approximations of fractional order operators used in control theory and applications”, Fractional Calculus and Applied Analysis, 3(3), 231-248.
  • Podlubny, I., (1999). “Fractional differential equations”, New York: Academic Press.
  • Zeinali, M., & A., Khajepour, (2010). “Height control in laser cladding using adaptive sliding mode technique: theory and experiment”, Journal of Manufacturing Science and Engineering, 132(4). https://doi.org/10.1115/1.4002023
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Makaleler
Authors

Kaan Can 0000-0002-6597-2797

Hayriye Sekban This is me 0000-0002-3085-7297

Kamil Orman 0000-0002-7236-9988

Abdullah Başçi 0000-0003-4141-2880

Publication Date August 31, 2020
Published in Issue Year 2020 Volume: 13 Issue: 2

Cite

APA Can, K., Sekban, H., Orman, K., Başçi, A. (2020). Design, Simulation and Comparison of Controllers for Temperature Profile Tracking Control of a Heat Flow System. Erzincan University Journal of Science and Technology, 13(2), 828-838. https://doi.org/10.18185/erzifbed.766645