Study of Intelligent Control Techniques Applied to a Stirring Tank with Heat Exchanger
( Vol-4,Issue-12,December 2017 )

Eduardo H. Kaneko, Matheus F. Mollon, Leandro A. Martins, Jonatas F. Dalmedico, Marcio A. F. Montezuma, Marcio Mendonca


Heat Exchanger, Fuzzy Logic Controller, Fuzzy Cognitive Maps, Artificial Neural Networks.


This work presents a study and evaluation of intelligent control techniques applied to the problem of temperature control of a stirring tank with heat exchanger. This problem is represented by the example provided and documented by MathWorks in MATLAB/Simulink software, called Heatex. The intelligent techniques used are Fuzzy Logic Controller (FLC), Fuzzy Cognitive Maps (FCM), Artificial Neural Networks (ANN) and the combination of these. The proportional-integral (PI) controller provided in the Heatex example is considered as a reference basis during the evaluation of the intelligent control techniques in different test scenarios. The metrics Integral of Absolute Error (IAE) and Integral Time-weighted Absolute Error (ITAE), as well as the parameters overshoot percentage and settling time are the criteria used to evaluate the control techniques performance.

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