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All Journal Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri J I M P - Jurnal Informatika Merdeka Pasuruan SENTIA 2015 Jurnal Informasi dan Teknologi Jurnal INOVTEKSeri Elektro The Journal of Artificial Intelligence and Development
Halim Mudia
Teknik Elektro Universitas Islam Negeri Sultan Syarif Kasim
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

 1 
Radial Basis Function Neural Network Control for Coupled Water Tank Halim Mudia
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 2 (2020): Spetember 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i2.10002

Abstract

The level and flow control in tanks are the heart of all chemical engineering system. The control of liquid level in tanks and flow between tanks is a basic problem in the process industries. Many times the liquids will be processed by chemical or mixing treatment in the tanks, but always the level of fluid in the tanks must be controlled and the flow between tanks must be regulated in presence of non-linearity. Therefore, in this paper will use neural network based on radial basis function (RBF) to control of  level 2 in the tank 2 with the setpoint of 10 centimeters and can follow the setpoint changes to 8 centimeters given in 225 seconds. The results show that neural netwotk based on radial basis function can follow setpoint given with steady state error is 0 cm, overshoot is 0%, rising time is 48 seconds, settling time is 52 seconds and can follow setpoint changes in 51 seconds.
Comparative Study of Mamdani-type and Sugeno-type Fuzzy Inference Systems for Coupled Water Tank Halim Mudia
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.9309

Abstract

The level and flow control in tanks are the heart of all chemical engineering system. The control of liquid level in tanks and flow between tanks is a basic problem in the process industries. Many times the liquids will be processed by chemical or mixing treatment in the tanks, but always the level of fluid in the tanks must be controlled and the flow between tanks must be regulated in presence of non-linearity. Threfore, in this paper will use fuzzy inference systems to control of  level 2 are developed using Mamdani-type and Sugeno-type fuzzy models. The outcome obtained by two fuzzy inference systems is evaluated. This paper summarizes the essential variation among the Mamdani-type and Sugeno-type fuzzy inference systems with setpoint of level is 10 centimeter. Matlab fuzzy logic toolbox is used for the simulation of both the models. This also confirms which one is a superior choice of the two fuzzy inference systems to control of level 2 in tank 2. The results show madani-type fuzzy inference system is superior as compared to sugeno-type fuzzy inference system.
Fuzzy Sugeno with Gain Compensator Based on Pole Placement for Controlling Coupled Water Tank System Halim Mudia; Ahmad Faisal; Marhama Jelita
Indonesian Journal of Artificial Intelligence and Data Mining Vol 5, No 1 (2022): March 2022
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v5i1.16350

Abstract

The control of liquid level in tanks is a classic problem in process industries. Most of the liquid will be processed by chemical or mixing treatment in the tanks. Because of that, the liquid level in the tanks must be regulated, so that in order for this system to work as we want, it needs a control strategy. Therefore, this research will use a control strategy using fuzzy sugeno with a gain compensator based on pole placement for controlling level of tank 2 in the coupled water tank system with setpoint is 10 centimeters at time 0 seconds and 8 centimeters given at time 1000 seconds. Wherein, the gain compensator based on pole placement is used to make the output system robust to changes in setpoint with zero steady-state error and fuzzy sugeno for faster time response. The results show that using the fuzzy sugeno with a gain compensator based on pole placement can follow setpoint given with 0 centimeters of steady-state error, 0% for overshoot, 44,6538 seconds for rising time, 62,2688 seconds for settling time and can follow setpoint changes in 58,8662 seconds.
Co-Authors Ahmad Faisal aulia rahma jumardi D.Iwan Riswandi Ek Iskandar Ewi Ewi Ismaredah faizal ahmad faizal Faizi, M Nur Hikmatul Amri Khamaludin, Khamaludin Mardiani, Eri Marhama Jelita Mochammad Rameli Ramadani Ramadani Rusdhianto Efendi Rusdhiyanto Effendie