Adaptive Neuro-Fuzzy Inference System (ANFIS) for Controlling Level and Pressure on Deaerator

*Sumardi Sumardi scopus  -  Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Indonesia
Munawar A Riyadi  -  Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Indonesia
Lintang Nurlitha Aprivirly  -  Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Indonesia
Revised: 10 Apr 2019; Accepted: 28 May 2019; Published: 11 Nov 2019; Available online: 30 Aug 2019.
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Language: EN
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DDeaerator is one of the most widely used plants in the chemical industry and marine steam power plant. Deaerator is used to eliminate oxygen in water that enters the boiler to avoid corrosion of the boiler pipes. Control of pressure and level in deaerator needs to be done to keep the process well. The purpose of the research is to design a control system that can keep pressure and level of deaerator on the set point un the presence of changes in the load and input systems. Deaerator should be controlled to keep its safety and efficiency. Adaptive Neuro-Fuzzy Inference System (ANFIS) is a combination of fuzzy logic control and neural network. Design of ANFIS requires an input-output data set obtained from a PI controller that is considered as a "teacher" for ANFIS for the learning process. The results of the simulation show that the system using ANFIS controller for controlling pressure and level deaerator in normal set point can produce very small maximum overshoot that is equal to 0% and small IAE value that is 7.898 for pressure, and 157.7 for level compared to PI

Keywords: Deaerator; level; pressure; ANFIS

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