Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB / Simulink

(1)

(2)

(3)

(4)

Document details

1 of 2

Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB / Simulink

(Conference Paper)

,

Department of Mechanical Engineering, Diponegoro University, Tembalang, Semarang, 50275, Indonesia

Abstract

The most widely used control strategy in industry is proportional integral derivative (PID) controller. The popularity of PID controllers can be attributed partly to their robust performance in a wide range of operating conditions and partly to their functional simplicity. One of the application is to control arm robot manipulator model by using DC

servo motor as actuator. This paper presents design of PID controller of DC servo motor using automated PID tuning by sisotool for higher order system and implement to the Arduino Mega 2560 via potentiometer by using Simulink Support Package for Arduino Hardware in MATLAB / Simulink . A better design of controller using fuzzy logic controller (FLC) is proposed. Simulation results are demonstrated. Performance analysis shows the eﬀectiveness of the proposed Fuzzy logic controller as compared to the PID controller. © 2014 IEEE.

SciVal Topic Prominence

Topic:

Prominence percentile: 35.879

Author keywords

DC Servo Motor Fuzzy Logic Controler Fuzzy Logic Toolbox PID Controler Sisotool

Indexed keywords

Engineering controlled terms:

Autonomous agents Computer circuits Controllers DC motors Electric control equipment Fuzzy logic Manipulators MATLAB Proportional control systems Robot applications Speed control Three term control systems Two term control systems Voltage dividers

Engineering uncontrolled terms

Dc servomotors Fuzzy logic controllers Fuzzy Logic Toolbox Higher-order systems Performance analysis PID Controler

Proportional integral derivative controllers Sisotool

◅ Back to results Next ▻



Export



Download



Print



E-mail



Save to PDF

⋆

Add to List More...

▻

View at Publisher

Proceedings of 2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014

9 January 2015, Article number 7005725, Pages 42-46

2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014; The Trans Luxury Hotel BandungBandung; Indonesia; 19 August 2014 through 21 August 2014; Category numberCFP1454Y-ART; Code 110034

Munadi  Akbar, M.A. 



View references (9)



Robots | Industrial robots | Robot arm



PlumX Metrics Usage, Captures, Mentions, Social Media and Citations beyond Scopus.

Metrics

27

Citations in Scopus

98th percentile

6.01

Field-Weighted Citation Impact

Cited by 27 documents

, ,

(2020) International Journal of Integrated Engineering

, ,

(2019) 2019 International Conference on Advanced Electrical Engineering, ICAEE 2019

, ,

(2019) Proceedings of 2018 3rd International Conference on Electrical Sciences and Technologies in Maghreb, CISTEM 2018

❓ View all metrics ▻



Fuzzy model reference adaptive controller for position control of a dc linear actuator motor in a robotic vehicle driver Mahdi, A.A.M.H. Salim, W.S.I.W. Farhan, K.H.M.

Design and Control of a Single- Phase Series Resonance Inverter using an Arduino Microcontroller Maamar, A.E.T. Helaimi, M.

Taleb, R.

Design of Real-Time PID tracking controller using Arduino Mega 2560for a permanent magnet DC motor under real disturbances.

Adel, Z. Hamou, A.A.

Abdellatif, S.

View all 27 citing documents

Brought to you by Universitas Diponegoro

Search Sources Lists SciVal ↗ Create account Sign in

(5)

References (9)

Engineering main heading:

Electric machine control

Rashidifar, M.A., Rashidifar, A.A., Ahmadi, D.

Modeling and control of 5 DOF robot arm using fuzzy logic supervisory control

(2013) International Journal of Robotics and Automation (IJRA), 2 (2), pp. 56-68. . June

Gaurav, A.K.

Comparison between conventional PID and fuzzy logic controller for liquid ﬂow control: Performance evaluation of fuzzy logic and PID controller by using MATLAB/simulink

(2012) International Journal of Innovative Technology and Exploring Engineering (IJITEE), 1 (1).

. June

Urrea, C., Kern, J.

A new model for analog servo motors

(2011) Canadian Journal on Automation, Control and Intelligent Systems, 2 (2). . March

Burns, R.S.

(2001) Advances Control Engineering Jordan Hill

Philips, C.L., Harbor, R.D.

(2000) Feedback Control Systems. . Prentice-Hall

Ogata, K.

(1970) Modern Control Engineering. . Prentice-Hall

ISBN: 978-147994802-4

Source Type: Conference Proceeding Original language: English

DOI: 10.1109/INAGENTSYS.2014.7005723 Document Type: Conference Paper

Publisher: Institute of Electrical and Electronics Engineers Inc.

▻ View in search results format All Export



^Print



^E-mail



Save to PDF Create bibliography

1

Cited 7 times

2

Cited 34 times

3

Cited 11 times

4

5

Cited 487 times

6

Cited 6226 times

Inform me when this document is cited in Scopus:

Introduction to fuzzy logic using MATLAB

Cited 574 times http://www.springerlink.com/openurl.asp?genre=book&isbn=978-3-540-35780-3

View at Publisher

8

9

Cited 34 times

◅ Back to results Next ▻  Top of page

About Scopus

What is Scopus Content coverage Scopus blog Scopus API Privacy matters

Language

⽇本語に切り替える切换到简体中文切換到繁體中文 Русский язык

Customer Service

Help Contact us

We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the .

Terms and conditions ↗ Privacy policy ↗ Elsevier B.V ↗

use of cookies

(7)

Proceedings of

2014 International Conference on

Intelligent Autonomous Agents, Networks and Systems (INAGENTSYS 2014)

August 19-21, 2014 | Bandung, Indonesia

IEEE Catalog Number: CFP1454Y-ART ISBN: 978-1-4799-4802-4

Organized by:

IEEE Indonesia Control System (CS) /

Robotics & Automation (RA) Joint Societies Chapter

(8)

Proceedings of

20 2 01 14 4 I I NT N TE ER RN N AT A TI IO O NA N AL L C C ON O NF FE ER R EN E NC CE E ON O N

IN I N TE T EL LL LI IG G EN E NT T A A UT U TO ON N O O MO M O U U S S A A G G EN E NT TS S, , NE N E T T WO W OR R KS K S A A ND N D SY S YS ST TE EM M S S

Copyright © 2014 by the Institute of Electrical and Electronics Engineers, Inc. All right reserved.

Copyright and Reprint Permission

Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limit of U.S. copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided the per-copy fee indicated in the code is paid through Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923

Other copying, reprint, or reproduction request should be addressed to IEEE Copyrights Manager, IEEE Service Center, 445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331

Catalog Number: CFP1454Y-ART ISBN: 978-1-4799-4802-4

Additional copies of this publication are available from:

Curran Associates, Inc.

57 Morehouse Lane Red Hook, NY 12571 USA +1 845 758 0400

+1 845 758 2633 (FAX)

Email: curran@proceedings.com

(9)

(10)

ii

CONFERENCE ORGANIZATION

Organizing Committee

General Chair : Endra Joelianto (Institut Teknologi Bandung, Indonesia) Co-General Chair : Arjon Turnip (Indonesian Institute of Sciences, Indonesia) Secretary Chair : M. Salehuddin (Institut Teknologi Bandung, Indonesia) Treasury Chair : Ary Murti (University of Telkom, Indonesia)

Technical Program Chair : Mclaurin Hutagalung (Institut Teknologi Harapan Bangsa, Indonesia) Publication Chair : Augie Widyotriatmo (Institut Teknologi Bandung, Indonesia)

International Program Committee

B. Riyanto T, Institut Teknologi Bandung, Indonesia Y. Y. Nazaruddin, Institut Teknologi Bandung, Indonesia Salmah, University of Gadjah Mada University, Indonesia A. Namatame, National Defense Academy of Japan, Japan Jacob Engwerda, Tilburgh University, Netherland, Netherland Saifur Rahman, Virginia Tech – Advanced Research Institute

M. Pipattanasomporn, Virginia Tech – Advanced Research Institute, USA R. K. Boel, Ghent University, Belgium

Keum-Shik Hong, Pusan University, Korea K. Kuk, University of Belgrade, Serbia

K. Chandrasekaran, National Institute of Technology Karnataka, Indi B. Iantovics, Petru Maior University, Romania

I. Mas, CONICET, Argentina

C. Kitts, Santa Clara University, USA K. Senthil Kumar, SRM University, India

M. Wang, The University of Hong Kong, Hong Kong, China L. Negreanu, University of Politechnica of Bucharest, Romania C. Chastagnol, University of Orsay 11, France

P. Bellot, Aix-Marseille University, France

D. Polajnar, University of Northern British Columbia, Canada

M. Santor, Universidad Complutense de Madrid, Spain

(11)

vii

WELCOME SPEECH i

CONFERENCE ORGANIZATION ii

LIST OF TECHNICAL PROGRAM COMMITTEE (TPC) & REVIEWERS iii

INAGENTSYS 2014 TECHNICAL PROGRAM v

TABLE OF CONTENTS vii

PLENARY SESSION

Survivability of Networkes Agents with Risk Sharing

Prof. Akira Namatame 1

Multi-Agent Models to Study the Robustness and Resilience of Complex Supply Chain Networks

Loganathan Ponnambalam; Do Huynh Long; Disha Sarawgi; Xiuju Fu; Rick Siow Mong Goh 7 PARALLEL SESSIONS

Agent communication, Network and Simulation

Control Simulation of an Automatic Turret Gun Based on Force Control Method

Mohamad Nasyir Tamara; Bambang Pramujati; Hendro Nurhadi; Endra Pitowarno 13 Implementation of Multi-Agent System Using Fuzzy Logic Towards Shopping Center Simulation

Jason Christian; Seng Hansun 19

Spectral Approach for Diffusion Phenomena Among Networked Agents

Kiyotaka Ide; Akira Namatame; Loganathan Ponnambalam; Xiuju Fu; Rick Siow Mong Goh 24

Organization, Perception and Adaptation

A New Approach of Quantum-Inspired Genetic Algorithm for Self-Generation of Fuzzy Logic Controller

Iksan Bukhori; Arthur Silitonga 30

Wall Following Control for the Application of a Brain-Controlled Wheelchair

Gunachandra; Sylvester Chrisander; Augie Widyotriatmo; Suprijanto 36

Simulation of Fuzzy Logic Control for DC Servo Motor Using Arduino Based on Matlab/Simulink

Munadi; M. Amirullah Akbar 42

Systems and Networks

Emergency-Aware and QoS Based Routing Protocol in Wireless Sensor Network

Siti Ummi Masruroh; Khadijah Utami Sabran 47

An ARCH Model the Electric Power of Extra High Voltage (EHV) Transmission Substation Forecasting in Cawang, Jakarta, Indonesia

Udjianna S. Pasaribu; Susi Setiyowati; Utriweni Mukhaiyar 52

Simple Method of Human Skin Detection Using HSV and YCbCr Color Spaces

Muhammad Arif Rahman; I Ketut Purnama; Mauridhi Purnomo 58

Index Author 62

(12)

5/5/2020 Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB/Simulink - IEEE Conference Publication

https://ieeexplore.ieee.org/document/7005723/authors#authors 1/3

Institutional Sign In

Conferences > 2014 International Conference...

2Author(s) Munadi ; M. Amirullah Akbar View All Authors

Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB/Simulink

Publisher: IEEE Cite This Cite This  PDF

13 Paper Citations

2624 FullText Views

Alerts

Manage Content Alerts

Add to Citation Alerts Export to

Collabratec

Abstract Document Sections I. Introduction II. ARM Robot

Manipulator Model III. DC Servo Motor

Description IV. Design of the Pid

Controller V. Design of

Proposed Fuzzy Logic Controller

Authors Figures References

Citations Keywords

Metrics M Lik Thi

Downl PDF

Abstract: The most widely used control strategy in industry is proportional integral derivative (PID) controller. The popularity of PID controllers can be attributed partly to thei... View more

Metadata

Published in: 2014 International Conference on Intelligent Autonomous Agents, Networks and Systems

Abstract:

The most widely used control strategy in industry is proportional integral derivative (PID) controller. The popularity of PID controllers can be attributed partly to their robust performance in a wide range of operating conditions and partly to their functional simplicity. One of the application is to control arm robot manipulator model by using DC servo motor as actuator. This paper presents design of PID controller of DC servo motor using automated PID tuning by sisotool for higher order system and implement to the Arduino Mega 2560 via potentiometer by using Simulink Support Package for Arduino Hardware in MATLAB/Simulink. A better design of controller using fuzzy logic controller (FLC) is proposed. Simulation results are demonstrated. Performance analysis shows the effectiveness of the proposed Fuzzy logic controller as compared to the PID controller.

Date of Conference: 19-21 Aug. 2014 Date Added to IEEE Xplore: 12 January 2015

INSPEC Accession Number: 14863360 DOI: 10.1109/INAGENTSYS.2014.7005723

More Like This

Optimization of fuzzy controllers for industrial manipulators via genetic algorithms

IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468)

Published: 2003

Research of 2-DOF planar parallel high speed/high accuracy robot

Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788) Published: 2004



Top Organizations with Patents on Technologies Mentioned in This Article

My Settings Get Help

Browse ^Subscribe

(13)

5/5/2020 Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB/Simulink - IEEE Conference Publication

IEEE Personal Account

CHANGE USERNAME/PASSWORD

Purchase Details

PAYMENT OPTIONS

VIEW PURCHASED DOCUMENTS

Proﬁle Information

COMMUNICATIONS PREFERENCES PROFESSION AND EDUCATION TECHNICAL INTERESTS

Need Help?

US & CANADA: +1 800 678 4333 WORLDWIDE: +1 732 981 0060 CONTACT & SUPPORT

Follow

  

More Like This

Authors



Figures



References



Citations



Keywords



Metrics



ISBN Information: Publisher: IEEE

Conference Location: Bandung, Indonesia Munadi

Department of Mechanical Engineering Diponegoro University Tembalang, Semarang 50275, Indonesia

M. Amirullah Akbar

I. Introduction

Industrial systems with high-efficiency and great performance have taken more advantages of robot technology. The large number of control research and many control applications were presented during the last years, concentrated on control of robotic systems. Robot manipulator field is one of the interested fields in industrial, educational and medical applications. It works in unpredictable, hazard and inhospitable circumstances which human cannot reach, such as, working in nuclear or chemical reactors is very dangerous, while when a robot instead human it involves no risk to human life [1]. Therefore, modeling and analysis system responses of DC servo motor as actuators in robot manipulators and applying control techniques such as FLC are very important before using them in these circumstances to a smooth precision movement of arm robot manipulator model. In some literature said that FLC have better stability and small overshoot [2].

Sign in to Continue Reading

Munadi

M. Amirullah Akbar

Contents

(14)

5/5/2020 Survivability of networked agents with risk sharing - IEEE Conference Publication

1Author(s) Akira Namatame View All Authors

Survivability of networked agents with risk sharing

84 Full Text Views

Alerts

Collabratec

Abstract Document Sections I. Introduction II. Models of

Cascade Failures and Risk Sharing III. Risk (Load)

Sharing Protocal IV. Survivability of

Networked Agents V. Conclusion

Authors References

Keywords Metrics More Like This

Downl PDF

Abstract: Our society is governed by complex socio-technological networks, biological networks, and social networks. Among them, telecommunication networks, power grids, water dist... View more

Metadata

Abstract:

Our society is governed by complex socio-technological networks, biological networks, and social networks. Among them, telecommunication networks, power grids, water distribution networks, transport networks or logistic networks are critical infrastructures that play a vital role in our modern society. It has become of paramount importance to understand and characterize the dynamic failures that might happen in these complex networks. We review, in detail, the previous work on cascade failure, and investigate the possibilities and constraints of creating decentralized and coordinated solution to the cascade failure problem. We demonstrate a few heuristics for mitigating cascading failure based on local-only knowledge actually do more harm than good. We then provide an effective method based on the concept of risk (load) sharing. We provide a simple micro-foundation based on coordinated incentives to absorb external shocks in order to survive collectively. The models of shock transfer are built up to investigate some stylized facts on how external or innate shocks tend to be allocated in the agent network, and how this allocation changes agents' failure probability. We analyze how risk sharing rules can actually affect the agent' resilience to external shocks. In particular, we focuses on: (i) how the allocation of risk is affected by the sharing rules, the network structure and the distribution of initial shocks among agents; (ii) how this allocation changes agents' failure probabilities.

More Like This

Combinatorial competing failure analysis considering random propagation time 2016 Annual Reliability and Maintainability Symposium (RAMS)

Published: 2016

Side-abrasion failure analysis of rod strings for water flooding pump oil wells 2009 8th International Conference on Reliability, Maintainability and Safety Published: 2009



Browse ^Subscribe

(15)

5/5/2020 Survivability of networked agents with risk sharing - IEEE Conference Publication

Purchase Details

PAYMENT OPTIONS

Need Help?

Follow

  

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

Authors



References



Keywords



Metrics



ISBN Information:

INSPEC Accession Number: 14850558 DOI: 10.1109/INAGENTSYS.2014.7005716 Publisher: IEEE

Conference Location: Bandung, Indonesia

Akira Namatame

Department of Computer Science National Defense Academy of Japan Yokosuka, Japan

I. Introduction

The phenomenon of cascade failure has been recognized in a wide variety of systems, including socio-technological networks, biological ecosystems, and financial systems. Indeed, any system that can be modeled using an interdependence graph with limited capacity of either nodes or edges to carry flow of some resource such as information, electrons, or energy, will be exhibit the cascade failure phenomenon.

Akira Namatame

IEEE Account

»Change Username/Password

»Update Address

Purchase Details

»Payment Options

»Order History

»View Purchased Documents

Profile Information

»Communications Preferences

»Profession and Education

»Technical Interests

Need Help?

»US & Canada: +1 800 678 4333

»Worldwide: +1 732 981 0060

»Contact & Support

Contents

(16)

5/5/2020 Multi-agent models to study the robustness and resilience of complex supply chain networks - IEEE Conference Publication

5Author(s) Loganathan Ponnambalam ; Do Huynh Long ; Disha Sarawgi ; Xiuju Fu ; R… View All Authors

Multi-agent models to study the robustness and resilience of complex supply chain networks

1 Paper Citation

212 FullText Views

Alerts

Collabratec

Abstract Document Sections 1. Introduction 2. Agent-Based

Modeling and Network Analysis 3. Network-Level

Metrics Comparison Between SCN1 and SCN2 4. Simulation of

Hypothetical Disruptions 5. Conclusion

Citations Keywords

Downl PDF

Abstract: Increase in the rate of disruptive events in the recent times and their economic implications on business continuity have raised the attention in supply chain disruption ... View more

Metadata

Abstract:

Increase in the rate of disruptive events in the recent times and their economic implications on business continuity have raised the attention in supply chain disruption research. Effective strategic planning during disruptions can be accomplished by assessing the robustness and resilience of the existing supply chain network. This talk will illustrate the application of multi-agent approach at modeling supply chain network as complex adaptive systems and investigating the supply chain network's structural characteristics via social network analysis. The proposed approach provides a better opportunity to achieve our objective - to understand the emergence of complex supply chain networks, assess the network vulnerability after its emergence and study the robustness, resilience of the network to hypothetical internal/external disruptive scenarios. Also, the intelligence of the associated entities, their decision making's influence on the network's emergance, its productivity and its structural characteristics at the network level will be addressed. Supply chain disruption management

researchers can use the proposed approach to evaluate the robustness of their network and assess its resilience for varying degrees of disruptions.

More Like This

Supply chain management: a multi-agent system for collaborative production planning

2005 IEEE International Conference on e- Technology, e-Commerce and e-Service Published: 2005

A Framework for the Development of Multi- Agent Systems in Supply Chain Management

2009 42nd Hawaii International Conference on System Sciences

Published: 2009



Browse ^Subscribe

(17)

5/5/2020 Multi-agent models to study the robustness and resilience of complex supply chain networks - IEEE Conference Publication

Metrics More Like This

Authors



ISBN Information:

INSPEC Accession Number: 14850553 DOI: 10.1109/INAGENTSYS.2014.7005717 Publisher: IEEE

Conference Location: Bandung, Indonesia Loganathan Ponnambalam

Computing Science, Institute of High Performance Computing, A∗STAR, Singapore Do Huynh Long

Interns, Computing Science, Institute of High Performance Computing, A∗STAR, Singapore

Disha Sarawgi

Xiuju Fu

Computing Science, Institute of High Performance Computing, A∗STAR, Singapore Rick Siow Mong Goh

Computing Science, Institute of High Performance Computing, A∗STAR, Singapore

1. Introduction

Supply chain network (SCN) of modern era are complex adaptive systems made up of interconnected and inter-dependent firms that involve in procurement, provision, processing of raw materials into finished products, distribution of final products to the customers (Lamming et al., 2000; Harland et al., 2001). A supply chain network consists of adaptive firms that actively exchange materials and information in their pursuit of maximized individual revenue (Choi et al., 2001). This results in supply chain's highly dynamic and interdependent nature (Nair et al., 2009). Hence, the interactions among entities determine the network's evolution and its resilience/robustness to disruption.

Loganathan Ponnambalam

Computing Science, Institute of High Performance Computing, A∗STAR, Singapore

Do Huynh Long

Disha Sarawgi

Xiuju Fu

Computing Science, Institute of High Performance Computing, A∗STAR, Singapore Contents

(18)

5/5/2020 Spectral approach for diffusion phenomena among networked agents - IEEE Conference Publication

5Author(s) Kiyotaka Ide ; Akira Namatame ; Loganathan Ponnambalam ; Fu Xiuju ; Ri… View All Authors

Spectral approach for diffusion phenomena among networked agents

39 FullText Views

Alerts

Collabratec

Abstract Document Sections I. Introduction II. Analytical

Frameworks of Probabilistic Diffusion on Networks III. Spectral Analysis

of Networks for Diffusion Dynamics IV. Verification

Simulation V. Conclusion

Keywords Metrics

M Lik Thi

Downl PDF

Abstract: Study on probabilistic diffusion among networked agent is gathering attentions because it can represent information diffusion phenomena in this well- interconnected societ... View more

Metadata

Abstract:

Study on probabilistic diffusion among networked agent is gathering attentions because it can represent information diffusion phenomena in this well-interconnected society that have been led by the development of the internet. In real world networks, modular structure is known as ubiquitous characteristics. And, in this paper, spectral properties of several networks, including modular networks, are precisely investigated and the influences from the spectral properties to the diffusion dynamics among the networked agents are discussed. Then we found that, although dynamics on networks have been often approximated utilizing only the largest eigenvalue of the adjacency matrix in the previous literatures, not only the largest eigenvalue but also the other eigenvalues need to be considered especially in the analysis of modular networks, which is verified by the comparisons between analytical results and numerical simulation results.

INSPEC Accession Number: 14850550 DOI: 10.1109/INAGENTSYS.2014.7005720

More Like This

Minimizing outage probability for a class of MIMO channels

2009 11th Canadian Workshop on Information Theory

Published: 2009

Class-Probability Based Semi-Supervised Dimensionality Reduction for Hyperspectral Images

2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS)

Published: 2018



Browse ^Subscribe

(19)

More Like This

Authors



ISBN Information: Publisher: IEEE

Conference Location: Bandung, Indonesia Kiyotaka Ide

Akira Namatame

Computing Science Institute of High Performance Computing, A∗STAR Singapore, Singapore

Fu Xiuju

Rick Siow Mong Goh

I. Introduction

Diffusion phenomena on complex networks have been getting more attentions because of the rapidly growth of well-connected society led by the development of the information technology or the transportation systems. Diffusion phenomena on complex networks have often been analyzed as probabilistic diffusion process among networked agents and many analytical models have been developed so far. However, it is reported that there still exists the difference between the results of analytical models and the real diffusion behaviors. Various approaches have been proposed to explain this unexpected behavior of diffusion phenomena in the real world. One of the primary approaches is to investigate the effect from network structures in which the diffusions take place. And, recent studies on diffusion processes in networks reveal that the topology of networks is critical. In this paper, we investigate spectral properties which reflect the topological features of networks among agents and its influences to diffusion dynamics among the networked agents. To investigate the influences from spectral property of networks, we precisely analyze the two indices which appear in the expression for the fraction of the infected nodes over the network. Based on our analytical results, we hypothesis that not only the largest eigenvalue of adjacency matrix but also the other non-largest eigenvalues need to be considered in analysis of dynamics on real networks, although only the largest eigenvalues has been usually used to approximate the diffusion dynamics in networks. Our investigations and numerical simulation results highlight the impacts from the non-largest eigenvalues are critical especially in the network with modular structure.

Kiyotaka Ide

Contents

(20)

Purchase Details

PAYMENT OPTIONS

Need Help?

Follow

  

Figures



References



Keywords



Metrics



Akira Namatame

Fu Xiuju

Rick Siow Mong Goh

IEEE Account

»Change Username/Password

»Update Address

Purchase Details

»Payment Options

»Order History

»View Purchased Documents

Profile Information

»Communications Preferences

»Profession and Education

»Technical Interests

Need Help?

»US & Canada: +1 800 678 4333

»Worldwide: +1 732 981 0060

»Contact & Support

(21)

Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB / Simulink

Document details

Simulation of fuzzy logic control for DC servo motor using Arduino based on MATLAB / Simulink

Abstract

SciVal Topic Prominence

Author keywords

Indexed keywords











⋆

▻

View references (9)





Metrics

27

6.01

Cited by 27 documents

Brought to you by Universitas Diponegoro

Search Sources Lists SciVal ↗ Create account Sign in

References (9)







Related documents

Introduction to fuzzy logic using MATLAB

About Scopus

Language

Customer Service

Proceedings of

2014 International Conference on

Intelligent Autonomous Agents, Networks and Systems (INAGENTSYS 2014)

August 19-21, 2014 | Bandung, Indonesia

IEEE Catalog Number: CFP1454Y-ART ISBN: 978-1-4799-4802-4

Organized by:

IEEE Indonesia Control System (CS) /

Robotics & Automation (RA) Joint Societies Chapter

Proceedings of

20 2 01 14 4 I I NT N TE ER RN N AT A TI IO O NA N AL L C C ON O NF FE ER R EN E NC CE E ON O N

IN I N TE T EL LL LI IG G EN E NT T A A UT U TO ON N O O MO M O U U S S A A G G EN E NT TS S, , NE N E T T WO W OR R KS K S A A ND N D SY S YS ST TE EM M S S

Copyright © 2014 by the Institute of Electrical and Electronics Engineers, Inc. All right reserved.

Copyright and Reprint Permission

Other copying, reprint, or reproduction request should be addressed to IEEE Copyrights Manager, IEEE Service Center, 445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331

Catalog Number: CFP1454Y-ART ISBN: 978-1-4799-4802-4

Additional copies of this publication are available from:

Curran Associates, Inc.

57 Morehouse Lane Red Hook, NY 12571 USA +1 845 758 0400

+1 845 758 2633 (FAX)

Email: curran@proceedings.com

ii

CONFERENCE ORGANIZATION

Organizing Committee

General Chair : Endra Joelianto (Institut Teknologi Bandung, Indonesia) Co-General Chair : Arjon Turnip (Indonesian Institute of Sciences, Indonesia) Secretary Chair : M. Salehuddin (Institut Teknologi Bandung, Indonesia) Treasury Chair : Ary Murti (University of Telkom, Indonesia)

Technical Program Chair : Mclaurin Hutagalung (Institut Teknologi Harapan Bangsa, Indonesia) Publication Chair : Augie Widyotriatmo (Institut Teknologi Bandung, Indonesia)

International Program Committee

M. Pipattanasomporn, Virginia Tech – Advanced Research Institute, USA R. K. Boel, Ghent University, Belgium

Keum-Shik Hong, Pusan University, Korea K. Kuk, University of Belgrade, Serbia

K. Chandrasekaran, National Institute of Technology Karnataka, Indi B. Iantovics, Petru Maior University, Romania

I. Mas, CONICET, Argentina

C. Kitts, Santa Clara University, USA K. Senthil Kumar, SRM University, India

M. Wang, The University of Hong Kong, Hong Kong, China L. Negreanu, University of Politechnica of Bucharest, Romania C. Chastagnol, University of Orsay 11, France

P. Bellot, Aix-Marseille University, France

D. Polajnar, University of Northern British Columbia, Canada

M. Santor, Universidad Complutense de Madrid, Spain

vii

TABLE OF CONTENTS

WELCOME SPEECH i

CONFERENCE ORGANIZATION ii

LIST OF TECHNICAL PROGRAM COMMITTEE (TPC) & REVIEWERS iii

INAGENTSYS 2014 TECHNICAL PROGRAM v

TABLE OF CONTENTS vii

PLENARY SESSION

Survivability of Networkes Agents with Risk Sharing

Prof. Akira Namatame 1

Multi-Agent Models to Study the Robustness and Resilience of Complex Supply Chain Networks

Loganathan Ponnambalam; Do Huynh Long; Disha Sarawgi; Xiuju Fu; Rick Siow Mong Goh 7 PARALLEL SESSIONS

Control Simulation of an Automatic Turret Gun Based on Force Control Method