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ITS » Master Theses » Sistem Pengaturan S2
Posted by hassane@its.ac.id at 26/05/2010 14:43:29  •  3793 Views


ANFIS-PI BASED ADAPTIVE PREDICTIVE CONTROL TO HEAT EXCHANGER TEMPERATURE

Author :
RUSLIM ( 2207202201 )




ABSTRAK

Permasalahan yang ada pada proses pengaturan temperatur Heat Exchanger adalah terbatasnya area kerja sensor dan aktuator pada plant tersebut. Keterbatasan area kerja ini akan menyebabkan keterlambatan respon dari sistem kontrol jika kontroler hanya berbasis pada sistem kontrol PID biasa. Pada penelitian ini dikembangkan sebuah Model Predictive Control menggunakan algoritma Intelligent Control System dengan fokus kajian berjudul Adaptive Predictive Control berbasis Neuro Fuzzy Inference System Proportional Integral ANFIS-PI untuk pengaturan temperatur Heat Exchanger. Kontroler yang didesain kemudian diujikan pada model plant Heat Exchanger dari Temperature Process Rig Trainer 38-600 dengan kondisi set point dan beban plant yang beruba-ubah. Hasil pengujian memperlihatkan bahwa kontroler yang telah didesain mampu berdaptasi dengan baik pada kondisi set point dan beban plant yang berubah-ubah di mana kesalahan tracking yang terjadi kurang dari 14 serta tidak terjadi osilasi pada sinyal respon dari plant.


ABSTRACT

The problems of Heat Exchanger temperature control process is the limited work area of censor and actuator on the plant. Limitation of this area will cause respon delay from the control systems if controler based only on PID control systems. This research would develop Model Predictive Control that used Intelligent Control System algorithm with focus of study was Adaptive Predictive Control based on Neuro Fuzzy Inference System and Proportional Integral ANFIS-PI of Heat Exchanger temperature controller. The performance of proposed controller then tested at Heat Exchanger plant of Temperature Process Rig Trainer 38-600 on changed plant setpoint and load condition. The tested result show that the proposed controller had better adapt on changed plant setpoint and load condition where tracking error wich seen is less than 14 and there is no oscillation of plant respon signals.



KeywordsPredictive control; ANFIS-PI predictive; Neuro fuzzy predictive
 
Subject:  Kontrol prediktif
Contributor
  1. Ir. Rusdhianto Effendie, AK, M.T.
  2. Ir. Ali Fatoni, M.T.
Date Create: 01/02/2010
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-22003100000221
Collection ID: 22003100000221
Call Number: RTE 629.8 Rus a


Source
Master Thesis of Electrical Engineering, RTE 629.8 Rus a, 2010

Coverage
ITS Community

Rights
Copyright @2010 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Master-10489-2207202201-Abstract_id.pdf - 156 KB
  2.  ITS-Master-10489-2207202201-Abstract_en.pdf - 157 KB
  3.  ITS-Master-10489-2207202201-Conclusion.pdf - 158 KB




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