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ITS » Undergraduate Theses » Teknik Fisika S1
Posted by ansi@its.ac.id at 18/06/2010 15:02:18  •  1586 Views


IMPLEMENTASI SISTEM KONTROL PREDIKTIF BERBASIS JARINGAN SYARAF TIRUAN SECARA ONLINE PADA PCT 13

Created by :
MUBAROK, MUHAMMAD NURDIN ( 2499100056 )



Subjectkontrol prediktif
Alt. Subject error steady state
Keywordprediktif kontrol
jaringan syaraf tiruan
optimasi
algoritma quasi newton
pct13

Description:

Sifat nonlinier yang dimiliki oleh proses sering menjadi kendala bagi penerapan sistem kontrol konvensional yang bersifat linier. Adanya pembatasan dalam perancangan kontroler seperti linierisasi, range operasi yang sempit menjadi alasan utama bagi performansi sistem kontrol linier yang kurang bagus. Salah satu usaha untuk meningkatkan performansi sistem kontrol adalah pengembangan sistem kontrol nonlinier berupa penerapan sistem kontrol berbasis model dengan menggunakan model nonlinier. Pada penelitian ini dikembangkan sistem kontrol nonlinier menggunakan algoritma sistem kontrol prediktif berbasis jaringan syaraf tiruan Komponen utama dari sistem kontrol prediktif adalah model proses, fungsi kriteria dan optimasi. Model digunakan untuk memprediksi output proses sepanjang horison prediksi. Fungsi obyektif digunakan untuk merepresentasikan performansi sistem kontrol, sedangkan algoritma optimasi digunakan untuk menentukan sinyal kontrol yang meminimumkan fungsi obyektif. Model nonlinier dari proses dicapai menggunakan jaringan syaraf tiruan. Strukur jaringan syaraf tiruan yang digunakan adalah MLP dengan algoritma belajar Levenberg Marquardt. Jaringan syaraf tiruan ini mampu memodelkan proses heat exchanger dengan RMSE = 0.0057. Sistem kontrol prediktif dikembangkan dengan menggunakan model nonlinier jaringan syaraf tiruan Algoritma optimasi Quasi Newton digunakan untuk mendapatkan sinyal kontrol yang akan diberikan pada proses. Berdasarkan simulasi yang dilakukan maka diperoleh parameter sistem kontrol prediktif yang digunakan secara online pada proses heat exchanger PCT 13. Hasil yang diperoleh menunjukkan bahwa sistem kontrol prediktif berbasis jaringan syaraf tiruan mampu mengatasi sifat nonlinier yang diniliki oleh proses dan memberikan performansi yang baik dengan nilai sebagai berikut: rire time(Tr) = 7O detik, maksimum overshoot (Mp) = 2,4 % settling time (Ts) = 94 detik dan error steady state (Ess) = 2.4 %.


Alt. Description

The nature of nonlinearity owned by process is often become the constraint for conventional control systems applying which have a linear characteristics. The limitation of design controller such as linearization, small range operation can make the performance of control system become unwell.The effort to increase performance of control systems is developing the nonlinear control system that in applying control system based on the model by using nonlinear model. It has been developed a nonlinear control system using predictive control system algorithm based on artificial neural network in this research. The main element of predictive control systems contain of a process model, objective function, and optimization of system. Model is used to predict process output as long as a prediction horizon. Objective function used to represent control system performance, while optimization system used to determine the control signaIs which can minimalist objective function The nonlinear model obtained by using the artificial neural network. The artificiaL neural network structures use Multilayer Perceptron (MLp) with the Levenberg Moryud training algoritlm. This artificial neural network able to noful the pr@ess of hea etthanger by RIwISE: 0.0057. The Prediaive control systemsd evebped by using Quasi Newton of Optimimtion algoritlxn which is uwd to get the corilrol signl to be pasred to the pruess According to the simulations, which have been accomplished, so thot the p&anebr of predictive confrol systcm by onltne can be obtaiwd at the heat erchfrtger process of PCT|3. The reslts tndicate that the predictive control systems based on ke dificial rmral network able to overcome the nature of nonlinewity owned by process utd give the good performance with the following ualue : rise time 8r) = 70 secon4 mmirrum wershoot (Mp)--2.4%, rettlingtine (Ts) = 94 recondmdenor suady stde (Els) = 2.4% Keywords : Predictive Control, Nearal Networks, Optimiution, Quasi Newbn Algoritlm, PCT I 3. lebih jelas lihat di abstract en

Contributor:
  1. BAMBANG LELONO W, ST.MT
  2. DR.Ir. TOTOK SUHARTANTO, DEA
Date Create:18/06/2010
Type:Text
Format:pdf
Language:Indonesian
Identifier:ITS-Undergraduate-3100004020651
Collection ID:3100004020651
Call Number:RSF 629.89 Mub i


Source :
Undergraduate Thesis, Physics Engineering, RSF 629.89 Mub i, 2004

Coverage :
ITS Community

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


Publication URL :
http://digilib.its.ac.id/implementasi-sistem-kontrol-prediktif-berbasis-jaringan-syaraf-tiruan-secara-online-pada-pct-13-11534.html




[ Free Download - Free for All ]

  1.  ITS-Undergraduate-11534-2499100056-Cover_en.pdf - 18 KB
  2.  ITS-Undergraduate-11534-2499100056-Approval_Sheet.pdf - 16 KB
  3.  ITS-Undergraduate-11534-2499100056-Abstract_id.pdf - 98 KB
  4.  ITS-Undergraduate-11534-2499100056-Preface.pdf - 66 KB
  5.  ITS-Undergraduate-11534-2499100056-Table_of_Content.pdf - 34 KB
  6.  ITS-Undergraduate-11534-2499100056-Illustration.pdf - 59 KB
  7.  ITS-Undergraduate-11534-2499100056-Tables.pdf - 16 KB
  8.  ITS-Undergraduate-11534-2499100056-Chapter1.pdf - 159 KB
  9.  ITS-Undergraduate-11534-2499100056-Conclusion.pdf - 58 KB
  10.  ITS-Undergraduate-11534-2499100056-Bibliography.pdf - 49 KB

[ FullText Content - Please, register first ]

  1. ITS-Undergraduate-11534-2499100056-Chapter2.pdf - 902 KB
  2. ITS-Undergraduate-11534-2499100056-Chapter3.pdf - 659 KB
  3. ITS-Undergraduate-11534-2499100056-Chapter4.pdf - 714 KB
  4. ITS-Undergraduate-11534-2499100056-Enclosure_A.pdf - 71 KB
  5. ITS-Undergraduate-11534-2499100056-Enclosure_B.pdf - 22 KB
  6. ITS-Undergraduate-11534-2499100056-Enclosure_C.pdf - 25 KB
  7. ITS-Undergraduate-11534-2499100056-Enclosure_D.pdf - 43 KB
  8. ITS-Undergraduate-11534-2499100056-Enclosure_E.pdf - 241 KB
  9. ITS-Undergraduate-11534-2499100056-Enclosure_F.pdf - 1289 KB
  10. ITS-Undergraduate-11534-2499100056-Enclosure_G.pdf - 1195 KB



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