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Analysis of Hybrid Temperature Control for Nonlinear Continuous Stirred Tank Reactor

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 336)

Abstract

Classical controllers usually require a prior knowledge of mathematical modeling of the process. The inaccuracy of mathematical modeling degrades the control performance of the continuous stirred tank reactor (CSTR), which shows nonlinearity to some extent. It is very necessary to attain desired temperature within a specified period of time to avoid overshoot and absolute error, with better temperature tracking capability, else the process is disturbed in the nonlinear CSTR system. This paper studies the output (temperature) tracking and disturbance rejection problem of nonlinear CSTR control systems with uncertainties via classical control PID, cascade control, and hybrid intelligent controller that includes FLC, adaptive control, and adaptive neuro-fuzzy inference system (ANFIS). This paper evaluates change in an adaptive controller response with varying adaptive gain. It has been observed that OLTF of CSTR is stable, and adaptive controller is best suitable for temperature control for ISE, and also has much better temperature tracking capability. Adaptive controller and ANFIS both have observed zero overshoot.

Keywords

  • CSTR
  • Nonlinearity
  • PID controller
  • Cascade controller
  • Adaptive controller
  • MIT rule
  • FLC
  • ANFIS

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Abbreviations

ρ :

Density of the material in the system lb/ft3

V :

Total volume of the system ft3

F :

Volumetric flow rate of the system ft3/h

C A :

Molar concentration (moles/volume) of component A in the system

r A :

Reaction rate per unit volume component A in the system

Q :

Amount of heat exchanged between the system and its surrounding per unit time

U :

Over all heat transfer coefficient

T st, T j :

Temperature of the steam and jacket, respectively

A H :

Total area of heat transfer

−∆H :

Heat of reaction at temperature T

References

  1. Zuhwar, Z.F.: The control of non isotherma CSTR using different controller strategies. Iraqi J. Chem. Pet. Eng. 13(3), 35–45 (2012)

    Google Scholar 

  2. Doyle III, F.J., Packard, A.K., Morari, M.: Robust controller design for a nonlinear CSTR. Chem. Eng. Sci. 44(9), 1929–1947 (1989)

    CrossRef  Google Scholar 

  3. Verma, O.P., Singla, R., Kumar, R.: Intelligent temperature controller for water bath system, WASET. Int. J. Comp. Sci. Eng. 6(9), 1232–1238 (2012)

    Google Scholar 

  4. Jain, P., Nigam, M.J.: Design of MRAC using modified MIT rule for a second order system. Adv. Electron. Electr. Eng. 3(4), 477–484 (2013)

    Google Scholar 

  5. Anbu, S., Jaya, N.: Design of adaptive controller based on Lyapunov stability for a CSTR. Int. J. Electr. Electron. Sci. Eng. 8(1), 183–186 (2014)

    Google Scholar 

  6. Zhang, T., Guay, M.: Adaptive nonlinear control of continuously stirred tank reactor systems. In: Proceeding of American Control Conference Arlington, pp. 1274–1279 (2001)

    Google Scholar 

  7. Pankaj, S., Kumar, J.S.: Comparative analysis of MIT rule and Lyapunov rule in model reference adaptive control scheme. Innovative Syst. Design Eng. 2(4), 154–162 (2011)

    Google Scholar 

  8. Abatneh, Y., Sahu, O.: Adaptive control design for a Mimo chemical reactor. Autom. Control Intel. Syst. 1(3), 64–70 (2013)

    Google Scholar 

  9. Ge, S.S., Hang, C.C., Zhang, T.: Nonlinear adaptive control using neural networks and its application to CSTR systems. J. Process Control 9, 313–323 (1998)

    CrossRef  Google Scholar 

  10. Raju, S.S., Siddiqa, M.A., Kiran, T.K.S.R., Viswanath, M.: Control of concentration in CSTR using DMC and conventional PID based on relay feedback system. Int. J. Eng. Sci. Tech. IJSET 5(4), 925–932 (2013)

    Google Scholar 

  11. San, K.Y., Stephanopoulos, G.: Optimal control policy for substrate-inhibited kinetics with enzyme deactivation in an isothermal CSTR. AIChE J. 29, 417–424 (1983)

    CrossRef  Google Scholar 

  12. Bequette, B.W.: Nonlinear control of chemical processes: a review. Ind. Eng. Chem. Res. 30, 1391–1413 (1991)

    CrossRef  Google Scholar 

  13. Elisante, E., Rangaiah, G.P., Palanki, S.: Robust controller synthesis for multivariable nonlinear systems with unmeasured disturbances. Chem. Eng. Sci. 59, 977–986 (2004)

    CrossRef  Google Scholar 

  14. Perez, M., Albertos, P.: Self-oscillating and chaotic behaviour of a PI-controlled CSTR with control valve saturation. J. Process Control 14, 51–59 (2004)

    CrossRef  Google Scholar 

  15. Bequette, B.W.: Process Control: Modeling, Analysis and Simulation, Module 8, 1st edn, pp. 641–657. Prentice Hall, Upper Saddle River (2003)

    Google Scholar 

  16. Bequette, B.W.: Process Dynamics: Modeling, Analysis and Simulation. Series in the Physical and Chemical Engineering Sciences, Module 7, 1st edn, pp. 506–524. Prentice Hall, Upper Saddle River (1998)

    Google Scholar 

  17. Coughanowr, D.R.: Process Systems Analysis and Control. Chemical Engineering Series, 2nd edn, pp. 282–287. McGraw-Hill International Editions (1991)

    Google Scholar 

  18. Stephanopoulos, G.: Chemical Process Control: A Introduction to Theory and Practice, 1st edn, pp. 395–402. PHI Learning, Upper Saddle River (1984)

    Google Scholar 

  19. Vasickaninova, A., Bakosova, M.: Cascade fuzzy control of a chemical reactor. In: Proceedings of 15th International Conference Process Control, Strbske Pleso, Slovakia, pp. 175-1–175-5 (2005)

    Google Scholar 

  20. Galluzo, M., Cosenza, B.: Control of a non-isothermal CSTR by type-2 fuzzy logic controllers, pp. 295–302. Springer, Berlin WILF (2009)

    Google Scholar 

  21. Gizi, A.J.H.A., Mustafa, M.W., Alsaedi, M.A., Zreen, N.: Fuzzy control system review. Int. J. Sci. Eng. Res. 4(1), 1–8 (2013)

    Google Scholar 

  22. Ioannou, P., Fidan, B.: Adaptive Control Tutorial, Chapter 1, pp. 1–11. Society for Industrial and Applied Mathematics, Philadelphia (2006)

    Google Scholar 

  23. Kumar, N., Khanduja, N.: Mathematical modelling and simulation of CSTR using MIT rule. In: IEEE 5th India International Conference on IICPE, Delhi, India, pp. 1–5 (2012)

    Google Scholar 

  24. Astrom, K.J., Wittenmark, B.: Adaptive Control, Chapter 5, 2nd edn, pp. 185–198. Pearson Publication (1995)

    Google Scholar 

  25. Astrom, K.J.: Adaptive Feedback Control. Proc. IEEE 75(2), 185–217 (1987)

    CrossRef  Google Scholar 

  26. Dostal, P., Bobal, V., Gazdos, F.: Simulation of nonlinear adaptive control of a continuous stirred tank reactor. Int. J. Math. Comp. Simul. 5(4), 370–377 (2011)

    Google Scholar 

  27. Prabhu, K., Bhaskaran, V.M.: Optimization of a control loop using adaptive method. IJEIT 1(3), 133–138 (2012)

    Google Scholar 

  28. Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Chapter 12, pp. 335–340. Prentice Hall, Upper Saddle River (1997)

    Google Scholar 

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Correspondence to Gaurav Manik .

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Prakash Verma, O., Kumar, S., Manik, G. (2015). Analysis of Hybrid Temperature Control for Nonlinear Continuous Stirred Tank Reactor. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 336. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2220-0_9

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  • DOI: https://doi.org/10.1007/978-81-322-2220-0_9

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