Abstract
Temperature is one of the most important and significant parameter of control in food processing, pharmaceuticals and in polymerization. The temperature process is highly nonlinear and design of robust controllers for such nonlinear systems is a challenge. This paper proposes a novel method for the control of temperature process. The traditional PI controllers which are in practice produce high overshoot and the design procedure seems complex. The proposed intelligent controller offers better performance in terms of overshoot and settling time and thus increases the robustness of the system. This paper describes the modeling of the temperature process in detail and discusses how the process responds to conventional and intelligent controllers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Huang, S.-J., Wang, C.-C.: Gain-scheduling fuzzy temperature controller for one-way input system. Transactions of the Institute of Measurement and Control 30, 451 (2008), doi:10.1177/0142331207086182
Renu, G., Subha Hency Jose, P.: Gain Scheduling and fuzzy Gain scheduling PI controller for temperature process. In: Proceedings of International Conference on Emerging Trends in Advanced Engineering Research (February 2012)
Adgar, A., Cox, C.S.: Practical Control Loop Tuning Using A Matlab/Simulink Toolbox. Control 2004, University of Bath, UK (September 2004)
Khare, Y.B., Singh, Y.: PID Control of Heat Exchanger System. International Journal of Computer Applications (0975 – 8887) 8(6), 975–8887 (2010)
Lee, C.C.: Fuzzy logic in control systems: Fuzzy logic controller-Part I. IEEE Trans. Syst. Man, Cybern. 20, 404–418 (1990)
LeBreux, M., Lacroix, M., Lachiver, G.: Fuzzy and feedforward control of an hybrid thermal energy storage system (received November 22, 2005; received in revised form January 18, 2006; accepted February 14, 2006)
Yazdani, M., Movahed, M.A., Mahmoudzadeh, S.: Applying a Novel Fuzzy-PI Controller on the Model of Continuous Stirred Tank Reactor, A. International Journal of Machine Learning and Computing 1(2) (June 2011)
Aslam, F., Kaur, G.: Comparative Analysis of Conventional, P, PI, PID and Fuzzy Logic ontrollers for the Efficient Control of Concentration in CSTR. International Journal of Computer Applications (0975 – 8887) 17(6) (March 2011)
Hangos, K., Cameron, I.: Process Modelling and Model Analysis. Process System Engineering 4, 20–36 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pamela, D., Jebarajan, T. (2012). Design of Intelligent Controller for Temperature Process. In: Kim, Th., Ko, Ds., Vasilakos, T., Stoica, A., Abawajy, J. (eds) Computer Applications for Communication, Networking, and Digital Contents. FGCN 2012. Communications in Computer and Information Science, vol 350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35594-3_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-35594-3_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35593-6
Online ISBN: 978-3-642-35594-3
eBook Packages: Computer ScienceComputer Science (R0)