Fuzzy Error Recovery in Feedback Control for Three Wheel Omnidirectional Soccer Robot
This paper is described one of the intelligent control method in Autonomous systems, which is called fuzzy control to correct the three wheel omnidirectional robot movement while it make mistake to catch the target. Fuzzy logic is especially advantageous for problems that can not be easily represented by mathematical modeling because data is either unavailable, incomplete or the process is too complex. Such systems can be easily up grated by adding new rules to improve performance or add new features. In many cases , fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. The fuzzy controller designed here is more accurate and flexible than the traditional controllers. The project is done at MRL middle size soccer robot team.
[1] Lotfi . Zadeh "theory of Fuzzy sets" 1965 university of California-
Berkeley.
[2] B.carter , M.Good,M . Dorohoff , J.Lew, R.L. WilliamsII,Paolo Gallina
"Mechanical Design and Modeling of an Omni-directional Robocup
Player" Department of mechanical Engineering Ohio University,
USA2002
[3] F.Riberio,I.Moutinho,P.silva,C.fraga,N.pereira "THREE OMNIDIRECTIONAL
WHEELS CONTROL ON A MOBILE ROBOT
"Control 2004,University of bath, UK, September 2004 (4) Rock
Hampton,QLD 4702,Australia
[4] M.Mohammadian & R.J.Stonier." Fuzzy Rule Generation by Genetic
Learning for Target Tracking", Proceeding of the 5th International
intelligent Systems Conference , Reno ,Nevada, 10-14 June,1996
[5] P.J Thomas,R.J Stonier "Fuzzy control in robot soccer evolutionary
learning in the first layer of control " Faculty of Informatics and
communication ,Central Queensland University.
[6] Tapio Frantti "Timing of fuzzy membership functions from data
"Department of process and Environmental Engineering , ISBN 951-42-
6434-7 ,ISSN 0355-3213 University of Oulu Press 2001.
[7] Navin Govind "Fuzzy Logic Control with the Intel 8xc196 Embedded
Microcontroller " Intel Corporation Chandler, AZ.
[8] E.H.Mamdani and S.Assilian, An Experiment in Linguistic synthesis
with a Fuzzy Logic Controller ,Fuzzy Reasoning and it-s Applications
.Academic Press,1981.
[9] B.Ravindran, P.Kachroo and T.Hegezay "Intelligent Feedback control-
Based adaptive resource Management for Asynchronous , Decentralized
Real Time Systems" Virginia polytechnic Institue and state university.
[10] Wei,Xinjiang Yantai Normal Univ.Jing,Yuanwei & Zhao ,Jun
Northeastern Univ." Robust Adaptive Fuzzy Controller for MIMO
nonlinear Systems" American Control Conference 2005.
[11] O.Cordon , F.Herrera, L.Magdalena and P.VIllar "A Genetic Learning
Process for Scaling Factors, Granularity and Contexts of the Fuzzy Rulebased
System Data Base Information Sciences" 136(2001)85-107.
[12] G.Procyk & E.Mamdani,"A Linguistic Self-Organizing Process
Controller "Automatica 15(1979)15-30.
[13] P.Xian-Tu, Generating Rules for Fuzzy Logic Controllers by Functions
Fuzzy Sets and Systems 36(1990)83-89.
[14] D.Simon "Sum Normal Optimization of Fuzzy Membership Function "
International Journal of Uncertainly ,Fuzziness and Knowledge - Based
Systems VOL.0,No,0(1993)World Scientific Publishing Company
Revised January 28, 2002.
[1] Lotfi . Zadeh "theory of Fuzzy sets" 1965 university of California-
Berkeley.
[2] B.carter , M.Good,M . Dorohoff , J.Lew, R.L. WilliamsII,Paolo Gallina
"Mechanical Design and Modeling of an Omni-directional Robocup
Player" Department of mechanical Engineering Ohio University,
USA2002
[3] F.Riberio,I.Moutinho,P.silva,C.fraga,N.pereira "THREE OMNIDIRECTIONAL
WHEELS CONTROL ON A MOBILE ROBOT
"Control 2004,University of bath, UK, September 2004 (4) Rock
Hampton,QLD 4702,Australia
[4] M.Mohammadian & R.J.Stonier." Fuzzy Rule Generation by Genetic
Learning for Target Tracking", Proceeding of the 5th International
intelligent Systems Conference , Reno ,Nevada, 10-14 June,1996
[5] P.J Thomas,R.J Stonier "Fuzzy control in robot soccer evolutionary
learning in the first layer of control " Faculty of Informatics and
communication ,Central Queensland University.
[6] Tapio Frantti "Timing of fuzzy membership functions from data
"Department of process and Environmental Engineering , ISBN 951-42-
6434-7 ,ISSN 0355-3213 University of Oulu Press 2001.
[7] Navin Govind "Fuzzy Logic Control with the Intel 8xc196 Embedded
Microcontroller " Intel Corporation Chandler, AZ.
[8] E.H.Mamdani and S.Assilian, An Experiment in Linguistic synthesis
with a Fuzzy Logic Controller ,Fuzzy Reasoning and it-s Applications
.Academic Press,1981.
[9] B.Ravindran, P.Kachroo and T.Hegezay "Intelligent Feedback control-
Based adaptive resource Management for Asynchronous , Decentralized
Real Time Systems" Virginia polytechnic Institue and state university.
[10] Wei,Xinjiang Yantai Normal Univ.Jing,Yuanwei & Zhao ,Jun
Northeastern Univ." Robust Adaptive Fuzzy Controller for MIMO
nonlinear Systems" American Control Conference 2005.
[11] O.Cordon , F.Herrera, L.Magdalena and P.VIllar "A Genetic Learning
Process for Scaling Factors, Granularity and Contexts of the Fuzzy Rulebased
System Data Base Information Sciences" 136(2001)85-107.
[12] G.Procyk & E.Mamdani,"A Linguistic Self-Organizing Process
Controller "Automatica 15(1979)15-30.
[13] P.Xian-Tu, Generating Rules for Fuzzy Logic Controllers by Functions
Fuzzy Sets and Systems 36(1990)83-89.
[14] D.Simon "Sum Normal Optimization of Fuzzy Membership Function "
International Journal of Uncertainly ,Fuzziness and Knowledge - Based
Systems VOL.0,No,0(1993)World Scientific Publishing Company
Revised January 28, 2002.
@article{"International Journal of Electrical, Electronic and Communication Sciences:54632", author = "Vahid Rostami and Omid sojodishijani and Saeed Ebrahimijam and Ali MohsenizanjaniNejad", title = "Fuzzy Error Recovery in Feedback Control for Three Wheel Omnidirectional Soccer Robot", abstract = "This paper is described one of the intelligent control method in Autonomous systems, which is called fuzzy control to correct the three wheel omnidirectional robot movement while it make mistake to catch the target. Fuzzy logic is especially advantageous for problems that can not be easily represented by mathematical modeling because data is either unavailable, incomplete or the process is too complex. Such systems can be easily up grated by adding new rules to improve performance or add new features. In many cases , fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. The fuzzy controller designed here is more accurate and flexible than the traditional controllers. The project is done at MRL middle size soccer robot team.
", keywords = "Robocup , omnidirectional , fuzzy control, soccer
robot , intelligent control.", volume = "1", number = "9", pages = "1321-4", }
