Fuzzy logic intelligent controlling concepts in industrial furnace temperature process control

This paper discusses the importance of fuzzy logic based intelligent controller designs for temperature process control of an Industrial furnace system. The performance of the proposed designs is evaluated with respect to the conventional PID controller. There are many tuning methods available to se...

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Bibliographic Details
Published in2012 IEEE International Conference on Advanced Communication Control and Computing Technologies pp. 353 - 358
Main Authors Vasu Murthy, B., Kumar, Y. V. Pavan, Kumari, U. V. Ratna
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Analytical models
Cascade control system
Dynamic performance analysis
Fuzzy Logic Controller
Manganese
Mathematical model
MATLAB
Matlab/Simlink
PID (Proportional plus Integral plus Derivative) controller
Temperature process control
Tuning
Tuning concepts
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ISBN1467320455
9781467320450
DOI10.1109/ICACCCT.2012.6320801

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Summary:This paper discusses the importance of fuzzy logic based intelligent controller designs for temperature process control of an Industrial furnace system. The performance of the proposed designs is evaluated with respect to the conventional PID controller. There are many tuning methods available to set the PID controller process gains. But these conventional methods are not effective in controlling non-linear processes like temperature. PID controller in cascaded architecture is the better choice compared to single loop control system for controlling these nonlinear processes. However, it is constrained in choosing the better PID gains. Also because of nonlinear and large inertia characteristics of the controller, often it doesn't produce satisfactory results. Hence, the research is going on for finding proper methods for overcoming these problems. This paper comprises the comparison of dynamic performance analysis of Conventional PID controller and fuzzy based intelligent controller. Conclusively, the performance of the proposed controller architecture is evaluated by finding the dynamic performance characteristics. The entire system is modeled by using MATLAB/Simulink, and the simulation results have shown that the proposed fuzzy logic controller has rapidity, good robustness and good dynamic performance.
ISBN:1467320455
9781467320450
DOI:10.1109/ICACCCT.2012.6320801