Adaptive Control of Temperature Inside Plug-Flow Chemical Reactor Using 2DOF Controller
- 1 Citations
- 1.2k Downloads
Abstract
The tubular chemical reactor is a industrial equipment widely used in the chemical or biochemical industry for production of various kinds of products. The mathematical model of such system is described by partial differential equations that are solved numerically. This article presents simulation results of the mean reactant’s temperature control inside the plug-flow tubular chemical reactor. The adaptive approach here is based on the recursive identification of the external linear model as a simplified mathematical representation of the originally nonlinear system. The control synthesis is based on the polynomial theory with the Pole-placement method and the spectral factorization. These methods are easily programmable and they also offers tuning of the controller. Used two degrees-of-freedom (2DOF) control structure divides the controller into two parts – the first in the feedback part and the second one in the feedforward part of the control loop.
Keywords
Adaptive control 2DOF Tubular chemical reactor Recursive identification Pole-placement methodNotes
Acknowledgment
This article was created with support of the Ministry of Education of the Czech Republic under grant IGA reg. n. IGA/CebiaTech/2018/002.
References
- 1.Russell, T., Denn, M.M.: Introduction to Chemical Engineering Analysis. vol. xviii, 502 p. Wiley, New York (1972) ISBN 04-717-4545-6Google Scholar
- 2.Ingham, J., Dunn, I.J., Heinzle, E., Penosil, J.E.: Chemical Engineering Dynamics. An Introduction to Modelling and Computer Simulation, 2nd edn. VCH Verlagsgesellshaft, Weinheim (2000)Google Scholar
- 3.Dostal, P., Prokop, R., Prokopova, Z., Fikar, M.: Control design analysis of tubular chemical reactors. Chem. Papers 50, 195–198 (1996)Google Scholar
- 4.Evans, L.C.: Partial Differential Equations. Graduate Studies in Mathematics, vol. 19, 2nd edn. American Mathematical Society, Providence (2010). ISBN 978-0821849743zbMATHGoogle Scholar
- 5.Vojtesek, J., Dostal, P.: Adaptive control of the tubular reactor with co-and counter-current cooling in the jacket. In: 23rd European Conference on Modelling and Simulation, Madrid, pp. 544-550 (2009). ISBN 978-0-9553018-8-9Google Scholar
- 6.Grimble, M.J.: Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems. Wiley, Hoboken (2006). ISBN 978-0-470-02073-9CrossRefGoogle Scholar
- 7.Astrom, K.J., Wittenmark, B.: Adaptive Control, 2nd edn. Prentice Hall, Reading (1994). ISBN 978-0201558661Google Scholar
- 8.Bobal, V., Bhm, J., Fessl, J., Machacek, J.: Digital Self-tuning Controllers: Algorithms. Implementation and Applications. Advanced Textbooks in Control and Signal Processing. Springer, London (2005). ISBN 1-85233-980-2Google Scholar
- 9.Stericker, D.L., Sinha, N.K.: Identifcation of continuous-time systems from samples of input-output data using the \(\delta \)-operator. Control Theor. Adv. Technol. 9, 113–125 (1993)Google Scholar
- 10.Mukhopadhyay, S., Patra, A.G., Rao, G.P.: New class of discrete-time models for continuos-time systeme. Int. J. Control 55, 1161–1187 (1992)CrossRefGoogle Scholar
- 11.Kucera, V.: Diophantine equations in control - a survey. Automatica 29, 1361–1375 (1993)MathSciNetCrossRefGoogle Scholar
- 12.Mikles, J., Fikar, M.: Process Modelling, Identification, and Control. Springer, Berlin (2007). ISBN 978-3-540-71970-0zbMATHGoogle Scholar