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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)


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.


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

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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


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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.

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