Abstract
Control of level in a process tank is most common in process and chemical industry. Development of model based control algorithms provides a better control under nonlinearities and disturbances. Identification is the process of estimating the model under given boundary conditions. Data driven empirical models are relatively easy to estimate and best suited within the process limitations. This paper deal with the design of an empirical model for a level control process and to tune the PID controller using different tuning method. The tuning method are compared between each other and the best control parameters are selected by analyzing the response.
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References
Donald, C.R., LeBlanc, E.S.: Process Systems Analysis and Control. McGraw-Hill, University of Michigan (1999)
Seborg, D.E., Edgar, T.F., Mellichamp, F.T.: Process Dynamic and Control. John Wiley & Son, New York (2004)
Ljung, L.: System identification-theory for the user. Prentice-Hall, Upper Saddle River, NJ (1994)
Viberg, M.: Subspace-based methods for the identification of linear time-invariant systems. Automatica 31, 1835–1851 (1995)
Ljung, L.: Estimating linear time-invariant models of nonlinear time varying systems. Eur. J. Control 7(2–3), 203–219 (2001)
Bai, E.W.: A blind approach to the Hammerstein–Wiener model identification. Automatica 38, 967–979 (2002)
Wang, D., Ding, F.: Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems. Comput. Math. Appl. 56, 3157–3164 (2008)
Marlin, E.T.: Process Control-Designing Processes and Control System for Dynamic Performance, pp. 175–206. McGraw-Hill, Ontario (1995–2014)
Stephanopoulos, G: Chemical Process Control-An Introduction to Theory and Practice. Prentice Hall India Learning Private Limited (2008)
Ziegler, J.G., Nichols, N.B., Rochester, N.Y.: Optimum settings for automatic controllers. Trans. ASME 64, 759–768 (1942)
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Philip, M.S., Krishna, B., Meenatchisundaram, S. (2019). Identification of Empirical Model and Tuning of PID Controller for a Level Control System. In: Ray, K., Sharan, S., Rawat, S., Jain, S., Srivastava, S., Bandyopadhyay, A. (eds) Engineering Vibration, Communication and Information Processing. Lecture Notes in Electrical Engineering, vol 478. Springer, Singapore. https://doi.org/10.1007/978-981-13-1642-5_35
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DOI: https://doi.org/10.1007/978-981-13-1642-5_35
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