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190 Fuzzy Logic Based Photovoltaic Peak Power Tracking Controller
Motivation Solar photovoltaic power is a prime alternative energy source candidate in several countries Solar power density with direct overhead incidence is 1 Kw/m2 High initial solar installation costs Low cell conversion efficiency (from 12% on ordinary units up to a maximum of 29% on very special ones) Prices for solar cells and power electronics are sharply decreasing There is an ever increasing energy demand, due to industrial development and population growth, motivating research and technological investments related to energy efficiency improvement and generation issues. The lower life cycle and maintenance of alternative resources can complement hydropower, fossil fuel and nuclear power generation. Solar photovoltaic power is a prime candidate in several countries where the solar power density with direct overhead incidence is 1 Kw/m2. Despite the high initial solar installation costs and a low cell conversion efficiency (from 12% on ordinary units up to a maximum of 29% on very special ones), the price for the solar cells and for power electronics are sharply decreasing which is expected to aid the acceptance of such systems. The solar array is generally connected to an energy storage system, which can be constituted by a system of batteries, fuel cells, flywheels, or even the distribution mains. The solar panel is subjected to varying solar intensity and changes in environmental temperature which, in turn, change the maximum power operating point. In order to speed up the amortization of installation costs, it is essential to extract the maximum power available on a continuous basis.

191 The solar array is generally connected to an energy storage system, which can be constituted by a system of batteries, fuel cells, flywheels, or even the distribution mains The solar panel is subjected to varying solar intensity and changes in environmental temperature which, in turn, change the maximum power operating point In order to speed up the amortization of installation costs, it is essential to extract the maximum power available on a continuous basis

192 Solar Vehicle Motivated a Lot the Development of this Fuzzy-PPT !

193 Photovoltaic System Block Diagram
Figure above shows a typical photovoltaic system. The solar array receives the sunlight and converts it to electricity by means of a power converter which contains a peak power tracking controller. An energy storage system and possible connections to a single-phase or three-phase utility are also provided. Usually the storage system is connected via a dc link, but very recently ac links using lossless resonant power converters have shown promises. Several schemes have been proposed for photovoltaic systems for residential applications and solar powered vehicles, and various different control strategies such as: (1) on-line conductance optimizers, that keep the power factor close to unit; (2) dynamic modeling for power maximization; and (3) fuzzy PI-controllers to replace conventional PI controllers in the feedback loop. Special power electronic inverters circuits have also been suggested for photovoltaic systems and solar arrays have been modeled for mathematical optimization, with emphasis on their physical properties.

194 Current x voltage for sunlight intensity variation
Solar cells are devices that convert photons into electrical potential in a PN silicon junction (or other material). Due to the very complex physical phenomena inside a solar cell, manufacturers usually present a family of operating curves (I-V), shown in the manufacturer curves above, with solar incidence and temperature as parameters. For every condition there is an unique point located at the knee of the I-V curve, at which the solar cell will generate maximum power. The figure also shows that the cell current density is a function of the voltage and that the curves can be displaced vertically by solar intensity, and horizontally by temperature variation. Current x voltage for temperature variation

195 Cell Equations where J is the current density (mA/cm2), v is the single voltage cell (V), vp is the total voltage (V) in the array, ip is the array current (A),  is the solar intensity (mW/cm2) and T is the temperature (oC). The parameters k1 (non-dimensional), k2 (mA/cm2)  (voltage coefficient V-1),  (temperature coefficient oC-1) and  (non-dimensional) are adjusted from the manufacturer curves with a multi-linear regression algorithm, where the parameters are calculated to minimize the quadratic error; Ncel is the number of cells in a series string connection that forms the array and Rs is the contact resistance between cells.

196 Modeling the solar array

197 Solar Array Driven by a Boost Converter
Figure above shows a PWM power boost converter that steps up the array voltage to a higher dc bus voltage.

198 Modeling the boost converter

199 Photovoltaic system static characteristics Output power, Efficiency Pout/Pin, Array impedance
The system was implemented in MATLAB/Simulink. The thirty-cell solar array supplied voltage to the boost converter which, in turn, delivered power to an equivalent output load. Initially the system was operated in open loop mode, in order to determine the behavior for various combinations of input variables and conditions. Figure above depict system static characteristics for three temperatures (0 oC, 25 oC, 60 oC) with a fixed load resistance of 100 and the solar intensity (l) varying gradually, from 10 mw/cm2 up to the maximum of 100mw/cm2. The shift of the peak power operating point is evident in such figures, as seen by the different duty-cycle (d) values for the peak power. (a) Output Power (b) Efficiency Pout/Pin (c) Normalized Array Impedance

200 Power due to load variation, for T=25oC and =100 mw/cm2
The figure shows power for three different load resistance values, at a fixed temperature (T=25oC) and solar intensity (l=100 mW/cm2) showing the duty-cycle where the power is maximum also changes with the equivalent load resistance.

201 Strategy for Optimizing Against Solar Intensity and Temperature Variation
Figure above shows the solar array current/voltage curves superimposed with a set of constant power curves, indicating the region of maximum power delivery for nominal solar intensity (l) and temperature (oC). The produced instantaneous power is given by the product of the dc link voltage with dc link current, and the power transferred to the dc link which equals the solar array power, (assuming a steady-state lossless system). This means that, for the particular parameters, the duty-cycle (d) of the boost power converter is to be varied to change the load line slope, i.e. the solar array impedance. In steady-state operation, it is desirable to adjust Z-1 so that the peak array power becomes available. Such an algorithm could be based on a look-up table which would either require an accurate solar array parameter estimation, or a step-by-step duty-cycle alteration. The latter is less favorable in as much as it may lead to a time-consuming search and a low-frequency oscillation around the optimum point.

202 Fuzzy Logic Based Solar Array Controller
The complete system block diagram is shown. The solar array and the boost power converter were modeled by their dynamic equations, while the fuzzy control algorithm was written and fine-tuned by simulations on the Simulink/Matlab environment. The fuzzy algorithm searches the maximum power heuristically, based on the meta-rule: “If the last change in the duty-cycle (DC) has caused the power to raise, keep moving the duty-cycle (DC) in the same direction; otherwise, if it has caused the power to drop, move it in the opposite direction.”

203 Tracking Rules IF DDCk is P AND DPk is PB THEN DDCk+1 is PB
IF DDCk is P AND DPk is PS THEN DDCk+1 is PM IF DDCk is N AND DPk is PB THEN DDCk+1 is NB IF DDCk is N AND DPk is PS THEN DDCk+1 is NM IF DDCk is P AND DPk is NB THEN DDCk+1 is NB IF DDCk is P AND DPk is NS THEN DDCk+1 is NM IF DDCk is N AND DPk is NB THEN DDCk+1 is PB IF DDCk is N AND DPk is NS THEN DDCk+1 is PM

204 Other rules are also necessary, due to the fact that the characteristic curves might change with temperature and sunlight level, leading to an overall shift of the optimum point. In order to keep track of this situation, the system must have the following rules: IF DDCk is Z AND DPk is PB THEN DDCk+1 is PM IF DDCk is Z AND DPk is PS THEN DDCk+1 is PS IF DDCk is Z AND DPk is NB THEN DDCk+1 is NM IF DDCk is Z AND DPk is NS THEN DDCk+1 is NS

205 Quantization Effect on the Power Search
It was found in the simulation studies that an important feature that provides an artificial inertia is needed in order to keep the system from stopping whenever a zero-crossing of the power is detected, leading to a tendency for ongoing motion for a few cycles. The usefulness of this set of rules becomes clear when one considers the quantization effect shown above. Since the input signals are digitized, the continuous curve is broken down into a series of plateaus. Clearly, the steeper the curve, the shorter the plateau. Since the optimum point tends to satisfy the condition dP/dDC = 0, the system might recognize any large plateau as a maximum power region, and stop.

206 The following rules have been identified for avoiding the stabilizing effect in a region other than that of true peak power: IF DDCk is P AND DPk is ZZ THEN DDCk+1 is PS IF DDCk is N AND DPk is ZZ THEN DDCk+1 is NS Finally, it is necessary to provide the system with a rule that stabilizes the point of operation at a peak power point: IF DDCk is Z AND DPk is ZZ THEN DDCk+1 is ZZ

207 Membership Functions for Fuzzy Search Controller

208 Rules with Different Degrees of Support

209 Solar intensity variation (l) and the corresponding dc-link current change with the fuzzy duty-cycle search

210 Illumination application

211 Test for various sunlight intensities
Collected power during one day

212 Fuzzy Based Photovoltaic System : Conclusion
A complete fuzzy logic solar array peak power tracking controller has been simulated, designed and implemented in the laboratory RISC microcontroller with a fuzzy algorithm that searches for the optimum duty-cycle that transfers the peak power from the solar array to a battery charger The advantages of the fuzzy controller are that the control algorithms give fast convergence and robust performance against parameter variation, and can accept noisy and inaccurate signals The system was found to reliably stabilize the maximum power transfer in all operating conditions and it is ready to be fitted in a larger installation.

213 A FEW MORE POWER ELECTRONICS APPLICATIONS….

214 Fuzzy Logic Based DC-Drive Control System
Main Features: Delta-alpha (Da) compensation for converter linearisation Makes converter characteristics independent of conduction region (discontinuous / continuous); Enables optimum current control design Fuzzy Current controller For better response than that obtainable with PI control;  Fuzzy Speed controller Less sensitive to load torque disturbances and inertia variations;

215 Fuzzy Logic Based DC-Drive Control System

216 Phase Controlled Discontinuous Operation Compensation

217 Fuzzy Logic Based Slip Gain Tuning
Main Features: Continuously identifies the rotor time constant, to track variations due to temperature or saturation effects; Combines the best characteristics of the Reactive Power model and D-axis Voltage model; Capable of performing well at any operating point in the torque-speed plane; Fast convergence; True value for tr

218 General block diagram for IVC system with slip gain tuning

219 Fuzzy Logic based slip gain tuning

220 List of Related Publications
SHORT COURSE AVAILABLE ON THE INTERNET Webcast lecture for Online Symposium for Electronics Engineers OSEE at “Introduction to Fuzzy Control” Available on-line at BOOK [1] “Fuzzy Modeling and Control” [Published in Portuguese: Controle e Modelagem Fuzzy] Authors: Ian S. Shaw and Marcelo G. Simoes Publisher: Edgard Bluchert, 1999  JOURNAL AND TRANSACTIONS PUBLICATIONS [1] M. Godoy Simoes, C. M. Furukawa, A. T. Mafra, J. C. Adamowski “A novel competitive learning neural network based acoustic transmission system for oil-well monitoring” IEEE Transactions on Industry Applications, March/April 2000, vol. 36, pp [2] M. Milanova, P.E.M. Almeida, J. Okamoto Jr., M. Godoy Simoes “Applications of cellular neural networks for shape from shading problem” Lecture Notes in Artificial Intelligence, Springer-Verlag, September, 1999, pp

221 [3] M. Godoy Simoes, N. N. Franceschetti, “Fuzzy optimisation based control of a solar array system” IEE Proceedings - Electric Power Applications, September 1999, Vol. 146, Issue 5, pp [4] M. Godoy Simões and M. Friedhofer, “An implementation methodology of a fuzzy based decision support algorithm,” International Journal of Knowledge-Based Intelligent Engineering Systems, October 1997, vol.1 no. 4, pp [5] M. Godoy Simões, “Intelligent control based vertical-axis wind turbine system” Revista Brasileira de Ciências Mecânicas, vol.XIX no. 4, pp , December/1997 [6] M. Godoy Simões, Bimal K. Bose and Ronald J. Spiegel, “Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system” IEEE Transactions on Industry Applications, July/August 1997, vol. 33, pp [7] G. C. D. Souza, B. K. Bose and M. Godoy Simões, “A simulation-implementation methodology of a fuzzy logic based control system” Revista da Sociedade Brasileira de Eletrônica de Potência, vol.2 no. 1, June 1997. [8] M. Godoy Simões, Bimal K. Bose and Ronald J. Spiegel, “Fuzzy logic based intelligente control of a variable speed cage machine wind generation system,” IEEE Transactions on Power Electronics, vol. 12, pp , Jan. 1997 [9] M. Godoy Simões and Bimal K. Bose, “Fuzzy neural network based estimation of power electronics waveforms” Revista da Sociedade Brasileira de Eletrônica de Potência, vol.1 no. 1, June 1996. 10] M. Godoy Simões and Bimal K. Bose, “Fuzzy neural network based estimation of power electronics waveforms” Revista da Soc. Brasi. de Eletr. e Potência, vol.1 no. 1, June 1996.

222 [11] M. H. Kim, M. Godoy Simões and B. K
[11] M.H. Kim, M. Godoy Simões and B. K. Bose,“Neural network based estimation of power electronic waveforms,” IEEE Transactions on Power Electronics, March/1996, vol. 11 No.2 , pp [12] M.G. Simões and B.K.Bose, “Neural network based estimation of feedback signals for a vector controlled induction motor drive,” IEEE Transactions on Industry Applications, May/June 1995, vol. 31, pp INTERNATIONAL CONFERENCE PAPERS – In English [1] P.E.M. Almeida and M. G. Simões “Fundamentals Of A Fast Convergence Parametric CMAC Network”, accepted for presentation at IJCNN’2001 (INNS-IEEE International Joint Conference on Neural Networks), Washington, DC, July 2001. [2] M. Godoy Simoes, J. L. M. Tiquilloca, H. M. Morishita, “Neural network based prediction of mooring forces in floating production storage and offloading systems” IEEE-IAS Annu. Meeting Conf. Rec., vol. 2, pp , Rome, Italy, October 2000. [3] M. Godoy Simoes, P. Vieira Jr., “Model development and design of a wheel-motor drive system” Proceedings of EPE - PEMC, vol. 5, pp , Kosice, Slovak Republic, September 5-7, 2000 [4] M. Godoy Simoes, Petronio Vieira Jr, “A High Torque Low-Speed Multi-Phase Brushless Machine - A Perspective Application for Electric Vehicles” ” IEEE-IECON International Conference on Industrial Electronics, Control and Instrumentation, Nagoya, Japan, October 2000.

223 [5] S. Szafir and M. Godoy Simoes, “Real time electrical motor control using DSP based system” IEEE Industrial Conference INDUSCON 2000, vol. 1, pp , Porto Alegre, Brazil, November 06-09, 2000 [6] M. Godoy Simões, N. N. Franceschetti, “A RISC microcontroller based photovoltaic system for illumination applications” IEEE-APEC Applied Power Electronics Conference, vol. 3, pp , New Orleans, Louisiana, February 6-10, 2000 [7] J. R. Pelaez, M. Godoy Simões “A computational model of synaptic metaplasticity” Proceedings of the International Joint Conference of Neural Networks. 1999, Paper number: 103 (CD-ROM Edition), Session 1.1, Washington D.C. [8] J. R. Pelaez, M. Godoy Simões “Pattern completion through thalamo-cortical interaction. Proceedings of the International Joint Conference of Neural Networks. 1999, Paper number: 102. (CD-ROM Edition), Session 1.3, Washington D.C. [9] J.R. Pelaez, M. G. Simoes, “A neural network based intruder detection system” 4o Brazilian Symposium on Intelligent Automation, September, 1999, pp , Sao Paulo, Brazil. [10] M. Milanova, P. E. M. Almeida, M. G. Simoes, “Applications of cellular neural networks to image understanding”, 4o Brazilian Symposium on Intelligent Automation, September, 1999, pp , Sao Paulo, Brazil. [11] M. Godoy Simoes, N. N. Franceschetti, M. Friedhofer, “A fuzzy logic based photovoltaic peak power tracking controller” IEEE-ISIE International Symposium on Industrial Electronics, vol. 1, pp , Pretoria, South Africa, July/1998

224 [12] C. Guestrin, F. G. Cozman, M
[12] C. Guestrin, F. G. Cozman, M. Godoy Simoes, “Industrial applications of image mosaicing and stabilization” IEEE-KES Knowledge-Based Intelligent Electronic Systems, vol. 2, pp , Adelaide, Australia, April/1998 [13] M. Godoy Simoes, N.N. Franceschetti, J.C. Adamowsky, “Drive system control and energy management of a solar powered electric vehicle” IEEE-APEC Applied Power Electronics Conference, Vol. 1, pp , Anaheim CA, February 15-19, 1998 [14] M. Friedhofer, M. Godoy Simoes, “Decision criteria with different degrees of importance: a contrast diffusion/intensification approach” 3o Simpósio Brasileiro de Automação Inteligente (SBAI’97) pp , Vitoria (Brazil), Sept. 1997 [15] M. Godoy Simoes, N. N. Franceschetti, J. C. Adamowski, “A photovoltaic based electric vehicle drive system”, 30th Int. Symp. on Automotive Technology and Automation - ISATA, pp , Florence, Italy, June 1997. [16] M. Godoy Simoes, Bimal K. Bose and Ron Spiegel, “Design and Performance Evaluation of a Fuzzy Logic Based Variable Speed Wind Generation System,” IEEE-IAS Annu. Meeting Conf. Rec., pp , San Diego, California, October 1996. [17] M. Godoy Simoes, Bimal K. Bose and Ron Spiegel, “Fuzzy Logic Based Variable Speed Wind Generation System,” XI Congresso Brasileiro de Automática, pp , vol. 1, Sao Paulo (Brazil), Sept. 1996 [18] M. Godoy Simoes and Bimal K. Bose, “Application of fuzzy neural networks in the estimation of distorted waveforms” IEEE International Symposium on Industrial Electronics, pp , Warsaw Poland, June/1996.

225 [19] M. Godoy Simoes and Bimal K
[19] M. Godoy Simoes and Bimal K. Bose, “Fuzzy neural network based estimation of power electronic waveforms,” III Congresso Brasileiro de Eletrônica de Potência (COBEP’95), pp , Sao Paulo (Brazil), Dec [20] G. C. D. Sousa, B. K. Bose and M. Godoy Simoes, “A Simulation-implementation methodology of a fuzzy logic based control system,” III Congresso Brasileiro de Eletrônica de Potência (COBEP’95), pp , Sao Paulo (Brazil), Dec [21] M.H. Kim, M. Godoy Simoes and B. K. Bose, “Neural network based estimation of power electronic waves,” IEEE/IECON Conf. Rec., pp , Orlando (USA), November 1995 [22] B.K. Bose, M. Godoy Simoes, D.R. Crecelius, K. Rajashekara, R. Martin, “Speed sensorless hybrid vector controlled induction motor drive,” IEEE/IAS Annu. Meeting Conf. Rec., pp , Orlando (USA), October 1995. [23] M. Godoy Simoes, B.K. Bose, and Ron Spiegel, “Fuzzy logic based intelligent control of a variable speed cage machine wind generation system,” IEEE Power Electronics Specialists Conference, pp , Atlanta (USA), June 1995. [24] M. Godoy Simoes and B.K. Bose; “Neural network based estimation of feedback signals for a vector controlled induction motor drive”, Industry Applications Society Annual Meeting (IEEE-IAS), vol. I, pp , Denver (USA), Oct [25] M. Godoy Simoes and B.K. Bose; “Application of fuzzy logic in the estimation of power eletronic waveforms” Industry Applications Society Annual Meeting (IEEE-IAS), vol. II, pp , Toronto Canada, Oct

226 BOOK CHAPTERS [1] “Speed Sensorless Hybrid Vector Controlled Induction Motor Drive” Book: Sensorless Control of AC Motor Drives, pages 119 to 125 Edited by K. Rajashekara et al… Publisher: IEEE Press, ISBN [2] “Neural Network Based Estimation of Feedback Signals for a Vector Controlled Induction Motor Drive” Book: Sensorless Control of AC Motor Drives, pages 248 to 257 SOUTH AND CENTRAL AMERICAN CONFERENCES – In Portuguese and Spanish [1] J. L. M. Tiquilloca, Hélio M. Morishita, Marcelo G. Simões, “Simulación Dinamica de Sistemas de Producción Flotante de Petróleo atraves de Redes Neuronales Artificiales”, [Dynamical simulation of oil well floating production systems with artificial neural networks], IV Jornadas Panamericanas de Automatización and V Jornadas de Sistemas de Instrumetación, Caracas, Venezuela, 8-12 de Mayo de 2000. [2] S. Szafir, M. Godoy Simoes, “Proposta de sistema simulador da dinâmica de veículos elétricos baseado em processador digital de sinais”, [Proposal of a digital signal processing based simulator system for electric vehicle dynamics], 4o Simp. Bras. de Autom. Intel. [4o Brazilian Symp. on Int. Automation], September, 1999, pp , Sao Paulo, Brazil.

227 [3] J. L. M. Tiquilloca, H. M. Morishita, M. G
[3] J. L. M. Tiquilloca, H. M. Morishita, M. G. Simoes, “Análise Dinâmica de Sistemas de produção Flutuante de Petróleo através de Redes Neurais Artificiais” [Dynamical analysis of floating production oil systems with artificial neural networks] 4o Simpósio Brasileiro de Automação Inteligente [4o Brazilian Symposium on Intelligent Automation], September, 1999, pp , Sao Paulo, Brazil [4] P. E. M. Almeida, M. G. Simoes, “Projeto de um Sistema Robótico Inteligente para Instalação de Equipamentos em Poços petrolíferos em Águas Profundas”, [Design of an intelligent robotic system for installation of equipments in deep sea oil wells] 4o Simpósio Brasileiro de Automação Inteligente [4o Brazilian Symposium on Intelligent Automation], September, pp , Sao Paulo, Brazil. [5] N.N. Franceschetti, L.O.M dos Reis, M. Godoy Simoes, “Modelagem e simulação da transferência de potência de um sistema fotovoltaico” [Modeling and simulation of photovoltaic system power transference] 4o Congresso Brasileiro de Eletrônica de Potência [4o Brazilian Power Electronics Conference] (COBEP’98) pp , Belo Horizonte, Brazil, December 1-5, 1997 [6] J. R. Peláez e M. Godoy Simoes, “Um novo algoritmo de busca heurística baseado no processamento do córtex cerebral” [A new heuristic search algorithm based on the cerebral cortex processing] 3o Simpósio Brasileiro de Automação Inteligente [3o Brazilian Symposium on Intelligent Automation] (SBAI’97) pp , Vitória, Brazil, September 3-5, 1997

228 [7] M. Godoy Simoes, L. E. B. da Silva , F. G. Cozman, V. F
[7] M. Godoy Simoes, L.E.B.da Silva , F.G. Cozman, V.F. Silva, “Proposta de controlador adaptativo para acionamento de um VAT utilizando a técnica de modelo de referência” [Proposal of adaptive controller for AGV drive system with a reference model technique], II Seminário Internacional de Motores Elétricos e Acionamentos Reguláveis, [II International Seminar in Electric Motors and Regulated Drives] (SIMEAR’97) vol.3, p , May, 1991 [8] M. Godoy Simões and N.N. Franceschetti, “Medição de corrente contínua com isolação aplicada à malha de torque de um servomotor cc” [Measurement of continuous current with isolation applied to the torque loop of a cc servomotor], [II International Seminar in Electric Motors and Regulated Drives] (SIMEAR’97), vol. 3 p , May, 1991 [9] M. Godoy Simões, J.C. Adamowski and F.G. Cozman, “Estratégia de acionamento de motores em veículos autônomos de transporte” [Motor drive system strategy for autonomous guided vehicles], 4o Congresso Nacional de Automação Industrial, [4o National Industrial Automation Congress](CONAI), pp , July 1990 [10] M. Godoy Simões, M. Martucci Jr., “Análise do desempenho de conversores chaveados visando a automação de projeto” [Performance analysis of switching converters aiming the automated design], 4o. Congresso Nacional de Automação Industrial, [4o National Industrial Automation Congress] (CONAI), pp , July 1990 [11] J.C. Adamowski, M. Godoy Simões and F.G. Cozman; “Desenvolvimento de um robô móvel” [Mobile robot development], 4o. CLACA - Cong. Latino Americano de Control Automático, Nov. 1990, Puebla-México, vol. 1 pp , also published in 8o. CBA - Congresso Brasileiro de Automática, vol. 1 pp , Sept. 1990, and in 4o. CONAI - Congresso Nacional de Automação Industrial, pp , July 1990

229 [12] F. G. Cozman, M. R. P. Barreto, P. E. Miyagi, J. C. Adamowski, M
[12] F.G. Cozman, M.R.P. Barreto, P.E. Miyagi, J.C. Adamowski, M. Godoy Simões and L.A. Moscato; “O projeto de veículos autônomos de transporte” [The project of autonomous vehicles for transportation], Simp. de Autom. Int. (SAI), pp , Curitiba, July 1990 [13] M. Godoy Simões, J.C. Adamowski and F.G. Cozman; “Acionamento e controle de motores para veículos autônomos de transporte” [Drive system motor control for autonomous guided vehicles] II Seminário de Eletrônica de Potência (SEP), pp , UFSC, Florianópolis, December 1989 [14] M. Godoy Simões and P.E. Miyagi; “Medianização aplicada em conversores chaveados” [Aplicattion of state space averaging in swicthing converters], 1o. Encontro Regional de Automação e Instrumentação (ERAI), pp. TMS01-TMS07, August 1989 [15] M. Godoy Simões and M. Martucci Jr.; “Automação da análise e modelamento de conversores chaveados” [Automation of analysis and modeling of switching power converters], 3o. Congresso Nacional de Automação Industrial (CONAI), pp , September 1988 [16] M. Godoy Simões and M. Martucci Jr.; “Topologias de conversores chaveados” [Switching power converters topologies], 4o. Congresso de Iniciação Científica e Tecnológica em Engenharia (CICTE), São Carlos, December 1985 [17] M. Godoy Simões and M. Martucci Jr., “Acionamento de motores de passo” [Stepping motors drives], 4o. Congresso de Iniciação Científica e Tecnológica em Engenharia (CICTE), São Carlos, December 1985 [18] M. Godoy Simões & M. Martucci Jr., “Fontes chaveadas para alimentação de sistemas digitais” [Switching power supplies for digital systems], 3o. Congresso de Iniciação Científica e Tecnológica em Engenharia (CICTE), São Carlos, December 1984

230 TECHNICAL MAGAZINES PUBLICATIONS (PORTUGUESE DIVULGATION)
[1] M. Godoy Simoes, Petronio Vieira Jr.; Acionamento de Veículos Elétricos [Electric vehicles drives] , Revista de Automação Industrial, no. 3, pp , July/August, 1998. [2] M. Godoy Simoes, Ian S. Shaw; As Vantagens da Aplicação da Lógica Fuzzy em Controle de Processos [The advantages of applying fuzzy logic in process control], Revista Eletricidade Moderna, pp , February/1998 [3] M. Godoy Simoes, N.N. Franceschetti, J.C. Adamowsky; Veículo Solar [Solar Vehicle], Revista Saber Eletrônica no. 300, pp. 1-7, January/1998 [4] M. Godoy Simoes, R. C. Giacomini; Software para Robótica” [Software for Robotics], Revista Controle e Instrumentação no. 191, 1987 [5] M. Godoy Simoes; “Configurações de Fontes Chaveadas” [Switching Power Supplies Configurations], Revista Nova Eletrônica no. 114, 1986 [6] M. Godoy Simoes; “Teoria de Fontes Chaveadas” [Switching Power Supplies Theory], Revista Nova Eletrônica, no. 101, 1985

231 List of Articles – Paulo E. M. Almeida
[1] Almeida, Paulo E. M. et alli. “Ambiente Integrado para Análise e Desenvolvimento de Controladores Difusos”, I Simpósio Brasileiro de Automação Inteligente, pp , 1993 (In Portuguese). [2] Almeida, Paulo E. M. “Implementação de um Ambiente de Desenvolvimento de Controladores Difusos e suas Aplicações em Controle de Processos Reais”, Master Thesis no. 147, P.P.G.E.E. / E.E.-U.F.M.G., (In Portuguese). [3] Almeida, Paulo E. M. et alli. “Utilização de um Ambiente de Desenvolvimento de Controladores Difusos em Controle de Processos Reais”, I Congresso Mineiro de Automação, pp , 1996 (In Portuguese). [4] Almeida, Paulo E. M. et alli. “A Novel Real Time Integrated Environment for the Design of Practical Fuzzy Controllers”. IEEE Second International Conference on Knowledge-Based Intelligent Electronic Systems, pp , Adelaide, AUSTRÁLIA, 1998. [5] Meireles, Magali R. G., Almeida, Paulo E. M. et alli. “Utilização de Lógica Difusa para o Controle de um Processo de Geração de Vapor”, II Congresso Mineiro de Automação, pp , Belo Horizonte, MG, 1998 (In Portuguese). [6] Meireles, Magali R. G., Almeida, Paulo E. M. et alli. “Identificação e Controle por Lógica Difusa da Malha de Combustível de um Processo de Geração de Vapor”, XII Congresso Brasileiro de Automática, Uberlândia, MG, 1998 (In Portuguese).

232 [7] Almeida, P. E. M. & PEREIRA, P. T. “Mapeamento de Sinais RF de Telefonia Celular através de Redes Neurais de Base Radial”, IV Simpósio Brasileiro de Automação Inteligente, pp , São Paulo, Setembro, 1999 (In Portuguese). [8] Milanova, M., Almeida, P. E. M. & SIMÕES, M. G. “Applications of Cellular Neural Networks to Image Understanding”, artigo apresentado em palestra convidada no IV Simpósio Brasileiro de Automação Inteligente, pp , São Paulo, Setembro, 1999 (In Portuguese). [9] Milanova, M., Almeida, P. E. M. et alli. “Applications of Cellular Neural Networks for Shape from Shading Problem”. In: PERNER, P. e PETROU, M. (Eds.) International Workshop on Machine Learning and Data Mining in Pattern Recognition, Lecture Notes in Artificial Intelligence, Springer-Verlag, pp , Leipzig, Germany, September, 1999. [10] Almeida, P. E. M. & Simões, M. G. “Fundamentals of a Fast Convergence Parametric CMAC Network”, To be presented at IJCNN’01, Washington, July, 2001.

233 List of Articles – Gilberto C. Drumond Sousa
[1] G. C. D. Sousa, B. K. Bose, J. G. Cleland, "Fuzzy logic based on-line efficiency optimization control of an indirect vector controlled induction motor drive", IEEE Transactions on Industrial Electronics, Vol. 42 No. 2, pp , abril de 1995. [2] G. C. D. Sousa, A. P. S. Santos, and A. B. Guimarães. "Vector-Controlled Drive System with Bi-directional Power flow and Unity Power Factor", Anais do Congresso Brasileiro de Eletrônica de Potência (COBEP’ 95), pp , São Paulo, SP, dezembro de 1995. [3] G. C. D. Sousa, B. K. Bose, and M. G. Simões, "A simulation-implementation methodology of a fuzzy logic based control system", Anais do Congresso Brasileiro de Eletrônica de Potência (COBEP’ 95), pp , São Paulo, SP, dezembro de 1995. [4] G. C. D. Sousa, "Fuzzy Logic Applications in Power Electronics and Drives-An Overview", Proc. of the 1995 Intern. Conf. on Ind. Electronics, Control, Instrumentation and Automation (IECON' 95), pp , Orlando, FL, 1995. [5] G. C. D. Sousa, "Fuzzy Logic in Power Electronics and Drives", Fuzzy Logica & de Elektrische Energietechniek, Leuwarden, Holanda, April, 1996. [6] G. C. D. Sousa, B. K. Bose, M. G. Simões, "A Simulation-Implementation Methodology of a Fuzzy Logic Based Control System", Eletrônica de Potência - SOBRAEP, Vol.2, No. 1, junho de 1997, pp [7] G. C. D. Sousa, D. R. Errera, "A High Performance Dynamometer for Drive Systems Testing", 23rd Int. Conf. on Industrial Electronics, Control, and Instrumentation, (IEEE-IECON'97) Conference Records, pp , New Orleans, Nov., 1997.

234 [8] A. L. Rabello, M. A. Có, G. C. D. Sousa, J. L. F
[8] A. L. Rabello, M. A. Có, G. C. D. Sousa, J. L. F. Vieira, "A Fully Protected Push-Pull Current Fed DC-DC Converter ", 23rd Int. Conf. on Industrial Electronics, Control, and Instrumentation, (IEEE-IECON'97) Conference Records, pp , New Orleans, Nov., 1997. [9] G. C. D. Sousa, F. A. Ferreira, "Controle Vetorial Direto Aplicado a um Conversor PWM Utilizando DSP: Análise, Implementação e Resultados", 4o Congresso Brasileiro de Eletrônica de Potência (COBEP' 97), pp , Belo Horizonte, Dez [10] G. C. D. Sousa, D. R. Errera, "A High Performance Test Bench for Drive Systems Development", 4o Congresso Brasileiro de Eletrônica de Potência (COBEP' 97), pp , Belo Horizonte, Dez [11] D. S. L. Simonetti, M. C. Azevedo, G. C. D. Sousa, J. L. F. Vieira "A Single Switch Three-Phase Boost Rectifier with Constant Input Harmonic Content", 24rd Int. Conf. on Industrial Electronics, Control, and Instrumentation, (IEEE-IECON'98) Conference Records, pp , Aachen, Alemanha, Set., 1998. [12] C. R. Cavati and G. C. D. Sousa, "Load Demand Level Estimation in Power Distribution Systems by Fuzzy Inference", Intelligent System Application to Power Systems (ISAP'99) Conference Records, pp , Rio de Janeiro, April, 1999. [13] G. C. D. Sousa and A. P. S. S. Rabello, " Application of the Luenberger Observer to the Sensorless Speed Control of an Induction Motor Drive: Analysis and Implementation", 5o Congresso Brasileiro de Eletrônica de Potência (COBEP' 99), pp , Foz do Iguaçu, Sept

235 [14] G. C. D. Sousa and N. S. Marcellos, "Application Aspects of Modern PWM AC Motor Drive Systems. Part I: Coupling Currents and Bearing Problems ", 5o Congresso Brasileiro de Eletrônica de Potência (COBEP' 99), pp , Foz do Iguaçu, Set [15] G. C. D. Sousa and N. S. Marcellos, Application Aspects of Modern PWM AC Motor Drive Systems Part II: Overvoltages and EMI Problems ", 5o Congresso Brasileiro de Eletrônica de Potência (COBEP' 99), pp , Foz do Iguaçu, Set [16] D. S. L. Simonetti, J. L. F. Vieira, G. C. D. Sousa, "Modeling of the High-Power-Factor Discontinuous Boost Rectifiers, IEEE Transactions on Industrial Electronics, Vol. 46 No. 4, pp , August,