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Robust fuzzy control design using genetic algorithm optimization approach:
Case study of spark ignition engine torque control
(Article), ,
Department of Electrical Engineering, Diponegoro University, Semarang, Indonesia
Abstract
In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed. The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optimal solution control at all operating points that generate uncertainties.
Optimal solution control at each operating point was calculated using genetic algorithm. A case study of engine torque control of spark ignition engine model was used to prove this new method of robust fuzzy control design.
From the simulation results, it can be concluded that the controller operates very well for a wide uncertainty. © 2017, University of Sistan and Baluchestan. All rights reserved.
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Prominence percentile: 48.536
Author keywords
Engine torque control Fuzzy logic Genetic algorithm Robust fuzzy control Spark ignition engine Takagi-Sugeno fuzzy model
Funding details
Funding sponsor Funding number Acronym
Universitas Diponegoro
261.5 /UN7.5/PP.1/2012
Direktorat Jenderal Pendidikan Tinggi
Funding text
The author would like to express their sincere gratitude to the Directorate General of Higher Education (DIKTI) and Diponegoro University (UNDIP) for the financial support received under the project of International Publication Research Grant Year 2012 by PNBP UNDIP (contract no. 261.5 /UN7.5/PP.1/2012).
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Open Access Iranian Journal of Fuzzy Systems
Volume 14, Issue 3, June-July 2017, Article number 2, Pages 1-13
Triwiyatno, A. Sumardi, S. Apriaskar, E.
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ISSN: 17350654 Source Type: Journal Original language: English
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Publisher: University of Sistan and Baluchestan
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TUTORIAL ON THE LQG/LTR METHOD.
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Triwiyatno, A., Nuh, M., Santoso, A., Sutantra, I.N.
Engine torque control of spark ignition engine using robust fuzzy logic control (2011) IACSIT Int. J. Eng. Technol., 3 (4), pp. 352-358. .
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Engine torque control of si engine using linear quadratic integral tracking (LQIT) Optimal Control (2011) IPTEK, 22 (4), pp. 190-197. .
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T-S fuzzy model design for engine torque control system of spark ignition engine (2009) Transmisi, 11 (4), pp. 177-182.
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7 of 16
Triwiyatno, A., Nuh, M., Santoso, A., Sutantra, I.N.
A new method of robust fuzzy control?: Case study of engine torque control of spark ignition engine (2011) Int. J. Acad. Res., 3 (5), pp. 178-185. .
Triwiyatno, A.; Department of Electrical Engineering, Diponegoro University, Semarang, Indonesia;
email:
© Copyright 2017 Elsevier B.V., All rights reserved.
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Iranian Journal of Fuzzy Systems
Scopus coverage years: from 2004 to Present Publisher: Unisity of Sistan & Baluchistan ISSN: 1735-0654
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Iranian Journal of Fuzzy Systems https://www.scimagojr.com/journalsearch.php?q=19700175219&tip=sid
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Iranian Journal of Fuzzy Systems https://www.scimagojr.com/journalsearch.php?q=19700175219&tip=sid
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Volume 14 Number 3 June 2017
University of Sistan and Baluchestan, Zahedan, Iran.
In the Name of God
IRANIAN JOURNAL OF FUZZY SYSTEMS
HONORARY CHAIRMAN
L. A. Zadeh, University of California, Berkeley, USA
EDITOR-IN-CHIEF
M. Mashinchi, Shahid Bahonar University of Kerman, Kerman, Iran
MANAGING EDITOR
R. A. Borzooei, Shahid Beheshti University, Tehran, Iran
EDITORIAL BOARD
N. R. Arghami, Mashhad, Iran J. Mordeson, Omaha, USA R. A. Borzooei, Tehran, Iran W. Pedrycz,Edmonton, Canada A. Daneshgar, Tehran, Iran M. K. Sen, Calcutta, India E. Eslami, Kerman, Iran F. G. Shi, Beijing, China
S. Katebi, Shiraz, Iran A. Vahidian Kamyad,Mashhad, Iran R. Langari, Doha, Qatar J. L. Verdegay,Granada, Spain M. Mashinchi, Kerman, Iran R. Viertl,Wien, Austria A. Memariani,Tehran, Iran M. M. Zahedi,Kerman, Iran R. Mesiar, Bratislava, Slovakia
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Iranian Journal of Fuzzy Systems (IJFS) is published two-monthly by the University of Sistan and Baluchestan. Annual subscription rates (including packing and postage) are as follows: for university departments, libraries, industrial and other multiple-reader institutions in Iran 900,000 Rials, in other countries 40 EURO; for individuals in Iran 700,000 Rials, in other countries 30 EURO. Reprints of papers are available for 150,000 Rials per copy in Iran and 2 EURO per copy elsewhere (Including packing and postage). For more information, please visit the website of the journal.
ﻪﻠﺠﻣ Iranian Journal of Fuzzy Systems (IJFS) هرﺎﻤﺷ ﻪﻣﺎﻧ ﻲﻃ
62 / 2910 / 3 خرﻮﻣ 26 / 1 / 83 نﻮﻴﺴﻴﻤﻛ
ﻪﺟرد رﻮﺸﻛ ﻲﻤﻠﻋ تﺎﻳﺮﺸﻧ ﻲﺸﻫوﮋﭘ ـ ﻲﻤﻠﻋ
دﻮﻤﻧ ﺖﻓﺎﻳرد زا و
ﺖﺳﻮﮔآ 2007 رد ﻲﻠﻠﻤﻟا ﻦﻴﺑ يدﺎﻨﺘﺳا هﺎﮕﻳﺎﭘ ISI
ﺖﺳا هﺪﺷ ﻪﻳﺎﻤﻧ .
Journal Address Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan, P.O. Box 98135-987 Zahedan, Iran.
Tel & Fax: +98-54-33431060 E-mail: [email protected] Homepage: http://ijfs.usb.ac.ir
A. Triwiyatno, S. Sumardi and E. Apriaskar
Robust Fuzzy Control Design Using Genetic Algorithm Optimization
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Persian Translation of Abstracts
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Volume & Issue: Volume 14, Issue 3, May and June 2017, Pages 1-177 1. Cover vol. 14, no. 3, June 2017-
View Article PDF 585.2 K
2. ROBUST FUZZY CONTROL DESIGN USING GENETIC ALGORITHM OPTIMIZATION APPROACH: CASE STUDY OF SPARK IGNITION ENGINE TORQUE CONTROL
Pages 1-13
Aris Triwiyatno; Sumardi Sumardi; Esa Apriaskar View Article PDF 582.39 K
3. TIME-VARYING FUZZY SETS BASED ON A GAUSSIAN MEMBERSHIP FUNCTIONS FOR DEVELOPING FUZZY CONTROLLER
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6. A COMMON FRAMEWORK FOR LATTICE-VALUED, PROBABILISTIC AND APPROACH UNIFORM (CONVERGENCE) SPACES
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7. GRADED DIUNIFORMITIES Pages 83-103
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8. STABILITY OF THE JENSEN'S FUNCTIONAL EQUATION IN MULTI-FUZZY NORMED SPACES
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9. THE CATEGORY OF T-CONVERGENCE SPACES AND ITS CARTESIAN-CLOSEDNESS Pages 121-138
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10. M-FUZZIFYING MATROIDS INDUCED BY M-FUZZIFYING CLOSURE OPERATORS Pages 139-149
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2 of 6 1/15/2021, 7:05 PM
ROBUST FUZZY CONTROL DESIGN USING GENETIC ALGORITHM
OPTIMIZATION APPROACH: CASE STUDY OF SPARK IGNITION ENGINE TORQUE CONTROL
Document Type : Research Paper Authors
Aris Triwiyatno ; Sumardi Sumardi ; Esa Apriaskar
Department of Electrical Engineering, Diponegoro University, Semarang, Indonesia Department of Electrical Engineering, Diponegoro University, Se- marang, Indonesia
10.22111/IJFS.2017.3238 Abstract
In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed.
The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optimal solution control at all operating points that generate uncertainties. Optimal solution control at each operating point was calculated using genetic algorithm. A case study of engine torque control of spark ignition engine model was used to prove this new method of robust fuzzy control design. From the simulation results, it can be concluded that the controller operates very well for a wide uncertainty.
Keywords
Fuzzy logic ; Robust fuzzy control ; Takagi-Sugeno fuzzy model ; Genetic Algorithm ; Engine torque control ; Spark ignition engine
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