Medical Oven Temperature Control Based on Soft Computing Techniques

https://doi.org/10.24237/djes.2016.09306

Authors

  • Intisar N. Al-Obaidi Department of Electrical Engineering, University of Technology-Baghdad, Iraq
  • Abbas H. Issa Department of Electrical Engineering, University of Technology-Baghdad, Iraq

Keywords:

Modeling, medical oven, PID, FLC, NN, ANFIS

Abstract

Different types of controllers are designed in this research to control the temperature of medical oven. These controllers represented by the conventional PID, the intelligent Neural Network (NN), Fuzzy-Logic controller (FLC) and the hybrid Adaptive-Neuro-Fuzzy-Inference-System (ANFIS) controller. The controllers designed using MATLAB R2012a version 7.14 both m-file and Simulink. Two laboratory ovens (lab ovens) with different mathematical models are used. A comparison between the designed controllers has been made, first with step response with the first oven and second with different set points of four medical applications for the second practical lab oven, the ANFIS superiority over the others has been proven which highlighted the hybridization power and efficiency and its suitability for controlling the temperature of medical oven.

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Published

2016-09-01

How to Cite

[1]
Intisar N. Al-Obaidi and A. H. Issa, “Medical Oven Temperature Control Based on Soft Computing Techniques”, DJES, vol. 9, no. 3, pp. 71–80, Sep. 2016.