UNIVERSIDADE TECNOLÓGICA FEDERAL DO PARANÁ PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E INFORMÁTICA INDUSTRIAL

SILVA, Marcio A. P. THREE COIL INDUCTIVE RESONANT LINK OPTIMIZATION FOR WIRELLES POWER TRANSFER. 94f. Dissertação – Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial. Universidade Tecnológica Federal do Paraná. Curitiba, 2017. Wireless power transfer through magnetic induction was first presented by Nikola Testla a century ago but, technical limitations did not let its immediate application at that time. It was only late of XX Century that commercial systems based on this technology could be offered. Nowadays this technology is considered the most appropriated to be used with portable devices like smartphones, tablets and so on. Additionally, it is the only technology available for dynamic charging of electric vehicles. In other words, charging while they are moving. In this kind of wireless power transfer technology, the energy transfer from the transmitter to the receiver is made through an electromagnetic link created by resonant coils. Several coils configurations can be used to implement the link. This work will focus on a system with threecoils assembled on axial alignment. The system performance will be evaluated in terms of power delivered to the load, efficiency and link distance. The three-coil system results will be compared with two-coil system results working under same operational conditions. That comparison points out the greater flexibility of three-coil system. This kind of system shows to be capable to function over a wider range of efficiency and power delivered to the load, which is not possible to the first one. Moreover, conditions under which the three-coil system shows to be more efficient, or able to deliver greater power to the load than two-coil system, will be discussed. Real data will be presented, as a case of a specific point of operation, in which the power delivered to the load is almost two times higher and efficiency is almost three times greater than the ones verified when using a two-coil system.

[1]  Soung Hie Kim,et al.  Fuzzy cognitive maps considering time relationships , 1995, Int. J. Hum. Comput. Stud..

[2]  Rayford B. Vaughn,et al.  Fuzzy cognitive maps for decision support in an intelligent intrusion detection system , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[3]  Gonzalo Pajares,et al.  Fuzzy Cognitive Maps for stereovision matching , 2006, Pattern Recognit..

[4]  Witold Pedrycz,et al.  Evolutionary Development of Fuzzy Cognitive Maps , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[5]  João Alberto Fabro,et al.  Fuzzy-neuro predictive control, tuned by genetic algorithms, applied to a fermentation process , 2003, Proceedings of the 2003 IEEE International Symposium on Intelligent Control.

[6]  N. K. Bose,et al.  Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .

[7]  Marco Colombetti,et al.  Behavior analysis and training-a methodology for behavior engineering , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[8]  Stephen Yurkovich,et al.  Fuzzy Control , 1997 .

[9]  A. Sarkar,et al.  Development of a fuzzy logic based mobile robot for dynamic obstacle avoidance and goal acquisition in an unstructured environment , 2005, Proceedings, 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics..

[10]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..

[11]  Ah-Hwee Tan,et al.  Integrated cognitive architectures: a survey , 2007, Artificial Intelligence Review.

[12]  L. Zadeh,et al.  An Introduction to Fuzzy Logic Applications in Intelligent Systems , 1992 .

[13]  Stephen E. Levinson,et al.  Vision-based reinforcement learning for robot navigation , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[14]  Chrysostomos D. Stylios,et al.  Fuzzy cognitive maps: a model for intelligent supervisory control systems , 1999 .

[15]  John B. Bowles,et al.  Using Fuzzy Cognitive Maps as a System Model for Failure Modes and Effects Analysis , 1996, Inf. Sci..

[16]  Graciano Dieck-Assad,et al.  Modeling and Simulation of a Fuzzy Supervisory Controller for an Industrial Boiler , 2006, Simul..

[17]  Sanming Zhou,et al.  Dynamic domination in fuzzy causal networks , 2006, IEEE Trans. Fuzzy Syst..

[18]  Chrysostomos D. Stylios,et al.  An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps , 2003, IEEE Transactions on Biomedical Engineering.

[19]  Gary G Yen,et al.  Reinforcement learning algorithms for robotic navigation in dynamic environments , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[20]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[21]  Andreas S. Andreou,et al.  A framework for developing intelligent decision support systems using evolutionary fuzzy cognitive maps , 2008, J. Intell. Fuzzy Syst..

[22]  Michael N. Vrahatis,et al.  Improving fuzzy cognitive maps learning through memetic particle swarm optimization , 2008, Soft Comput..

[23]  Yo-Ping Huang,et al.  Guard heuristic by dynamic fuzzy reasoning model for Chinese chess , 1995, Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society.

[24]  Chrysostomos D. Stylios,et al.  Modeling complex systems using fuzzy cognitive maps , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[25]  Michael N. Vrahatis,et al.  Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization , 2005, Journal of Intelligent Information Systems.

[26]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[27]  Chrysostomos D. Stylios,et al.  A Soft Computing Approach for Modelling the Supervisor of Manufacturing Systems , 1999, J. Intell. Robotic Syst..

[28]  A. Ismael,et al.  Fuzzy neural network implementation of self tuning PID control systems , 1994, Proceedings of 1994 9th IEEE International Symposium on Intelligent Control.

[29]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[30]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[31]  N. Peric,et al.  A reinforcement learning approach to obstacle avoidance of mobile robots , 2002, 7th International Workshop on Advanced Motion Control. Proceedings (Cat. No.02TH8623).

[32]  J.A.B. Tome,et al.  Rule based fuzzy cognitive maps-qualitative systems dynamics , 2000, PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500).

[33]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[34]  C. Stylios,et al.  A Combined Fuzzy Cognitive Map and Decision Trees Model for Medical Decision Making , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[35]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[36]  Y. C. Huang,et al.  Application of fuzzy causal networks to waste water treatment plants , 1999 .

[37]  Konstantinos G. Margaritis,et al.  Cognitive Mapping and Certainty Neuron Fuzzy Cognitive Maps , 1997, Inf. Sci..

[38]  Luke Fletcher,et al.  Reinforcement learning for a vision based mobile robot , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[39]  Bart Kosko,et al.  Virtual Worlds as Fuzzy Cognitive Maps , 1994, Presence: Teleoperators & Virtual Environments.

[40]  D. E. Koulouriotis,et al.  Learning fuzzy cognitive maps using evolution strategies: a novel schema for modeling and simulating high-level behavior , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[41]  Peihua Qiu,et al.  Fuzzy Modeling and Fuzzy Control , 2006, Technometrics.

[42]  Chunyan Miao,et al.  Transformation of Cognitive Maps , 2010, IEEE Transactions on Fuzzy Systems.

[43]  Kun Chang Lee,et al.  A cognitive map simulation approach to adjusting the design factors of the electronic commerce web sites , 2003, Expert Syst. Appl..

[44]  Witold Pedrycz,et al.  Genetic learning of fuzzy cognitive maps , 2005, Fuzzy Sets Syst..

[45]  Dimitris E. Koulouriotis,et al.  Comparing simulated annealing and genetic algorithm in learning FCM , 2007, Appl. Math. Comput..

[46]  Karl Perusich,et al.  Fuzzy cognitive maps for policy analysis , 1996, 1996 International Symposium on Technology and Society Technical Expertise and Public Decisions. Proceedings.

[47]  Adriane Beatriz de Souza Serapião,et al.  Fundamentos de otimização por inteligência de enxames: uma visão geral , 2009 .

[48]  Robin R. Murphy,et al.  Introduction to AI Robotics , 2000 .

[49]  Masafumi Hagiwara,et al.  Extended fuzzy cognitive maps , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[50]  Mostafa Jafari,et al.  Learning FCM by Tabu Search , 2007 .

[51]  Roseli A. Francelin Romero,et al.  A Hierarchical Self-Organizing Controller for Navigation of Mobile Robots , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[52]  H.A. Ryaciotaki-Boussalis,et al.  Neural network implementation to control systems: a survey of algorithms and techniques , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[53]  P.M. Jones,et al.  Modelling physical systems using fuzzy inference cognitive maps , 2004, IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04..

[54]  Ching-Hung Lee,et al.  Tuning of PID controllers for unstable processes based on gain and phase margin specifications: a fuzzy neural approach , 2002, Fuzzy Sets Syst..

[55]  C. Stylios,et al.  Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[56]  Leandro dos Santos Coelho,et al.  Projeto e estudo de caso da implementação de um sistema de controle nebuloso , 2003 .

[57]  Adil Baykasoglu,et al.  Training Fuzzy Cognitive Maps via Extended Great Deluge Algorithm with applications , 2011, Comput. Ind..

[58]  Shuji Asami.  Robots in Japan: present and future , 1994, IEEE Robotics & Automation Magazine.

[59]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[60]  Manolis A. Christodoulou,et al.  Fuzzy cognitive network: A general framework , 2007, Intell. Decis. Technol..

[61]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[62]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[63]  C. S. George Lee,et al.  Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems , 1996 .

[64]  Rehan Sadiq,et al.  INTERPRETING FUZZY COGNITIVE MAPS (FCMs) USING FUZZY MEASURES TO EVALUATE WATER QUALITY FAILURES IN DISTRIBUTION NETWORKS , 2006 .

[65]  Anthony G. Pipe,et al.  An architecture for building "potential field" cognitive maps in mobile robot navigation , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[66]  Zhi-Qiang Liu,et al.  Contextual fuzzy cognitive map for decision support in geographic information systems , 1999, IEEE Trans. Fuzzy Syst..

[67]  Lotfi A. Zadeh,et al.  Fuzzy Algorithms , 1968, Inf. Control..

[68]  Voula C. Georgopoulos,et al.  Introducing the theory of fuzzy cognitive maps in distributed systems , 1997, Proceedings of 12th IEEE International Symposium on Intelligent Control.

[69]  Zhi-Qiang Liu,et al.  On causal inference in fuzzy cognitive maps , 2000, IEEE Trans. Fuzzy Syst..

[70]  T. C. Callai,et al.  Controle nebuloso adaptativo por modelo de referência: projeto e aplicação em sistemas não lineares , 2007 .

[71]  Luis T. Aguilar,et al.  Intelligent Control of an Autonomous Mobile Robot using Type-2 Fuzzy Logic , 2006, Eng. Lett..

[72]  Lúcia Valéria Ramos de Arruda,et al.  A Combined FCM-GA Approach to Supervise Industrial Process , 2009 .

[73]  Rolf Dieter Schraft.  Mechatronics and robotics for service applications , 1994, IEEE Robotics & Automation Magazine.

[74]  Michael Glykas.  Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Applications , 2010 .

[75]  Leslie Pack Kaelbling,et al.  Reinforcement learning for robot control , 2002, SPIE Optics East.

[76]  Marley Maria Bernardes Rebuzzi Vellasco,et al.  Modelo Neuro-Fuzzy Hierrquico Politree com aprendizado por reforo para agentes inteligentes , 2007 .

[77]  Joseph Aguilar-Martin,et al.  Process situation assessment: From a fuzzy partition to a finite state machine , 2006, Eng. Appl. Artif. Intell..

[78]  Hua-Qing Min,et al.  Probability Fuzzy Cognitive Map for Decision-Making in Soccer Robotics , 2006, 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

[79]  P.J. King,et al.  The application of fuzzy control systems to industrial processes , 1977, Autom..

[80]  Chunyan Miao,et al.  Dynamical cognitive network - an extension of fuzzy cognitive map , 2001, IEEE Trans. Fuzzy Syst..

[81]  Bir Bhanu,et al.  Real-time robot learning , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[82]  Fernando A. Gomide,et al.  Redes neurais artificiais para engenharia e ciências aplicadas: curso prático , 2012 .

[83]  Dimitris E. Koulouriotis,et al.  Development of dynamic cognitive networks as complex systems approximators: validation in financial time series , 2005, Appl. Soft Comput..

[84]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[85]  Michael N. Vrahatis,et al.  A first study of fuzzy cognitive maps learning using particle swarm optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[86]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[87]  Mohammed Ismail,et al.  Virtual Worlds as Fuzzy Dynamical Systems , 1998 .

[88]  Paulo Cesar,et al.  DESENVOLVIMENTO DE UMA METODOLOGIA DE SINTONIA DE CONTROLADORES "FUZZY" UTILIZANDO REDES NEURAIS. APLICAÇÕES EM PROCESSOS PETROQUÍMICOS , 2001 .

[89]  Wai-Kiang Yeap,et al.  Using a Mobile Robot to Test a Theory of Cognitive Mapping , 2008, Robotics and Cognitive Approaches to Spatial Mapping.

[90]  Dilip Kumar Pratihar,et al.  Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches , 2006, Fuzzy Sets Syst..

[91]  Voula C. Georgopoulos,et al.  Fuzzy cognitive map architectures for medical decision support systems , 2008, Appl. Soft Comput..

[92]  Lin Chun-Mei.  Using fuzzy cognitive map for system control , 2008 .

[93]  Chrysostomos D. Stylios,et al.  Fuzzy Cognitive Maps in modeling supervisory control systems , 2000, J. Intell. Fuzzy Syst..

[94]  Aníbal Ollero,et al.  The autonomous mobile robot AURORA for greenhouse operation , 1996, IEEE Robotics Autom. Mag..

[95]  Guus Schreiber,et al.  Knowledge Engineering and Management: The CommonKADS Methodology , 1999 .