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Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "ANFIS CONTROLLER"

1

Sangeetha, J., and P. Renuga. "Recurrent ANFIS-Coordinated Controller Design for Multimachine Power System with FACTS Devices." Journal of Circuits, Systems and Computers 26, no. 02 (November 3, 2016): 1750034. http://dx.doi.org/10.1142/s0218126617500347.

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Анотація:
This paper proposes the design of auxiliary-coordinated controller for static VAR compensator (SVC) and thyristor-controlled series capacitor (TCSC) devices by adaptive fuzzy optimized technique for oscillation damping in multimachine power systems. The performance of the coordinated control of SVC and TCSC devices based on feedforward adaptive neuro fuzzy inference system (F-ANFIS) is compared with that of the adaptive neuro fuzzy inference system (ANFIS) structure based on recurrent adaptive neuro fuzzy inference system (R-ANFIS) network architecture. The objective of the coordinated controller design is to tune the parameters of SVC and TCSC fuzzy lead lag compensator simultaneously to minimize the deviation of rotor angle and rotor speed of the generators. The performance of the system is enhanced by optimally tuning the membership functions of fuzzy lead lag controller parameter of the flexible AC transmission system (FACTS) by R-ANFIS controller. The training data for F-ANFIS and R-ANFIS are generated by conventional linear control technique under various operating conditions. The offline trained controller tunes the parameter of lead lag controller in online. The oscillation damping ability of the system is analyzed for three-machine test system by calculating the standard deviation and cost function. The superior performance of R-ANFIS controller is compared with various particle swarm optimization-based feedforward ANFIS controllers available in literature.
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2

Rosyid, Abdur, Mohanad Alata, and Mohamed El Madany. "Adaptive Neuro-Fuzzy Inference System Controller for Vibration Control of Reduced-Order Finite Element Model of Rotor-Bearing-Support System." International Letters of Chemistry, Physics and Astronomy 55 (July 2015): 1–11. http://dx.doi.org/10.18052/www.scipress.com/ilcpa.55.1.

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Анотація:
This paper evaluates the use of adaptive neuro-fuzzy inference system (ANFIS) controller to suppress the vibration in a rotor-bearing-support system, and compare the performance to LQR controller. ANFIS combines the smooth interpolation of fuzzy inference system (FIS) and the learning capability of adaptive neural network. The ANFIS controller design starts with initialization which includes loading the training data and generating the initial FIS. In this case, the gain values obtained from the LQR controller design previously conducted were used as training data for the ANFIS controller. After the training data is provided, the ANFIS controller learns through a certain optimization algorithm to adjust the parameters. In the current work, hybrid algorithm was used due to its faster convergence. To evaluate the performance, the ANFIS output was compared to the training data. From the evaluation, it can be concluded that ANFIS controller can replace LQR controller with no need to solve the LQR’s Riccati equation. However, in the initialization process, it needs training data obtained from LQR control design. Furthermore, ANFIS controller can replace more than one LQR controllers with different weighting matrices Q and/or R. In a more general tone, ANFIS controller can serve as an effective controller, given any arbitrary speed-gain pairs as its training data. Finally, ANFIS controller can serve as a better controller than LQR as long as tuning can be conducted adequately for that purpose.
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3

Rosyid, Abdur, Mohanad Alata, and Mohamed El Madany. "Adaptive Neuro-Fuzzy Inference System Controller for Vibration Control of Reduced-Order Finite Element Model of Rotor-Bearing-Support System." International Letters of Chemistry, Physics and Astronomy 55 (July 3, 2015): 1–11. http://dx.doi.org/10.56431/p-q1glae.

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Анотація:
This paper evaluates the use of adaptive neuro-fuzzy inference system (ANFIS) controller to suppress the vibration in a rotor-bearing-support system, and compare the performance to LQR controller. ANFIS combines the smooth interpolation of fuzzy inference system (FIS) and the learning capability of adaptive neural network. The ANFIS controller design starts with initialization which includes loading the training data and generating the initial FIS. In this case, the gain values obtained from the LQR controller design previously conducted were used as training data for the ANFIS controller. After the training data is provided, the ANFIS controller learns through a certain optimization algorithm to adjust the parameters. In the current work, hybrid algorithm was used due to its faster convergence. To evaluate the performance, the ANFIS output was compared to the training data. From the evaluation, it can be concluded that ANFIS controller can replace LQR controller with no need to solve the LQR’s Riccati equation. However, in the initialization process, it needs training data obtained from LQR control design. Furthermore, ANFIS controller can replace more than one LQR controllers with different weighting matrices Q and/or R. In a more general tone, ANFIS controller can serve as an effective controller, given any arbitrary speed-gain pairs as its training data. Finally, ANFIS controller can serve as a better controller than LQR as long as tuning can be conducted adequately for that purpose.
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4

Nguyen, V. H., H. Nguyen, M. T. Cao, and K. H. Le. "Performance Comparison between PSO and GA in Improving Dynamic Voltage Stability in ANFIS Controllers for STATCOM." Engineering, Technology & Applied Science Research 9, no. 6 (December 1, 2019): 4863–69. http://dx.doi.org/10.48084/etasr.3032.

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Анотація:
One of STATCOM’s advantages is its quick response to disturbances in the power systems. The controller of STATCOM is commonly a PID controller. However, the PID controller is usually only highly effective at one or some operation points. In order to improve operational efficiency of the controller of STATCOM, the proposed ANFIS-PSO and ANFIS-GA controllers have been studied and applied to the studied power system. To demonstrate the performance of the proposed controllers, simulations of the voltage response in time-domain were performed in MATLAB to evaluate the effectiveness of the designed controllers for STATCOM. The simulation results showed that the proposed controllers can be used to improve the system stability as well as the voltage quality more effectively than the conventional PID controller. The ANFIS PSO controller carried out the best response after the occurrence of a three-phase short circuit fault.
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5

Salman, Saddam Subhi, Abdulrahim Thiab Humod, and Fadhil A. Hasan. "Dynamic voltage restorer based on particle swarm optimization algorithm and adaptive neuro-fuzzy inference system." Bulletin of Electrical Engineering and Informatics 11, no. 6 (December 1, 2022): 3217–27. http://dx.doi.org/10.11591/eei.v11i6.4023.

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Анотація:
This article uses a dynamic voltage restorer to tackle a wide range of power quality issues, such as voltage drooping and swelling, spikes, distortions, and so on. The proportional controller, integrated controller (PI), and adaptive neuro-fuzzy inference system (ANFIS) are proposed dynamic voltage restorer (DVR) controllers. The control strategy's goal is to employ an injection transformer to mitigate for the needed voltage and keep the load voltage fixed. The settings of the PI controller are fine-tuned using two methods: trial and error and intelligent optimum. Particle swarm optimization (PSO) is now the most effective method. In terms of settling time, overshoot, undershoot, and disturbances around the final value, the PSO-tuned PI controller outperforms the trial-and-error PI controller. The ANFIS controller is used to regulate the DVR's responsiveness through the PI-PSO controller. The PI-PSO data is used as training data by the ANFIS controller. The results show that a DVR with an ANFIS controller outperforms a PI-PSO controller in terms of overshoot, undershoot spike voltage, steady state time, and settling time. In the case of a failure voltage, the DVR with an ANFIS controller has a 27% undershoot spike voltage while the PI-PSO controller has a 30% undershoot spike voltage.
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6

Kharola, Ashwani, and Pravin P. Patil. "Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers." International Journal of Fuzzy System Applications 6, no. 4 (October 2017): 21–32. http://dx.doi.org/10.4018/ijfsa.2017100102.

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Анотація:
Elastic Inverted Pendulum system (EIP) are very popular objects of theoretical investigation and experimentation in field of control engineering. The system becomes highly nonlinear and complex due to transverse displacement of elastic pole or pendulum. This paper presents a comparison study for control of EIP using fuzzy and hybrid adaptive neuro fuzzy inference system (ANFIS) controllers. Initially a fuzzy controller was designed, which was used for training and tuning of ANFIS controller using gbell shape membership functions (MFs). The performance of complete system was evaluated through output responses of settling time, steady state error and maximum overshoot. The study also highlights effect of varying number of MFs on training error of ANFIS. The results showed better performance of ANFIS controller compared to fuzzy controller.
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7

B S, Manohar, and Banakara Basavaraja. "ANFIS based hybrid solar and wave generator for distribution generation to grid connection." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 1 (March 1, 2019): 479. http://dx.doi.org/10.11591/ijpeds.v10.i1.pp479-485.

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Анотація:
With a long coastal border of about 7500 Kms, India would need an efficient option of hybrid power generation in the coastal region. Abundant availability of wave power and sunlight due to its closeness to equator makes it clear base for power generation from wave generator and the solar power. This paper develops the implementation, which combines both the wave generator and the PV array for a hybrid power delivery controlled using Adaptive Neuro Fuzzy Inference Engine (ANFIS) controller. The super capacitor is used for higher efficiency compared to batteries. It absorbs power and delivers power fast, where it is more important in wave generation as the power and voltage is not stable. The power delivery improvement in this hybrid system while different controllers like the PI and the ANFIS controller is analysed. There is a higher power delivery improvement when ANFIS controller is chosen.
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Intidam, Abdessamad, Hassan El Fadil, Halima Housny, Zakariae El Idrissi, Abdellah Lassioui, Soukaina Nady, and Abdeslam Jabal Laafou. "Development and Experimental Implementation of Optimized PI-ANFIS Controller for Speed Control of a Brushless DC Motor in Fuel Cell Electric Vehicles." Energies 16, no. 11 (May 29, 2023): 4395. http://dx.doi.org/10.3390/en16114395.

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Анотація:
This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference system (PI-ANFIS) and particle swarm optimization-proportional integral-adaptive neuro-fuzzy inference system (PSO-PI-ANFIS)). The control objective is to regulate the rotor speed to its desired reference value in the presence of load torque disturbance and parameter variations. The proposed controller uses a dSPACE platform (MicroLabBox controller board). The experimental prototype comprises a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 52 A) and a brushless DC motor BLDC of 1 kW 1000 rpm. The PSO-PI-ANFIS controller presents better performance than the PI-ANFIS and classical PI controllers due to its ability to optimize the PI-ANFIS controller’s parameters using the particle swarm optimization (PSO) algorithm. This optimization results in improved tracking accuracy and reduced overshoot and settling time.
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Shahid, Muhammad Arslan, Ghulam Abbas, Mohammad Rashid Hussain, Muhammad Usman Asad, Umar Farooq, Jason Gu, Valentina E. Balas, Muhammad Uzair, Ahmed Bilal Awan, and Tanveer Yazdan. "Artificial Intelligence-Based Controller for DC-DC Flyback Converter." Applied Sciences 9, no. 23 (November 26, 2019): 5108. http://dx.doi.org/10.3390/app9235108.

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Анотація:
This paper presents an intelligent voltage controller designed on the basis of an adaptive neuro-fuzzy inference system (ANFIS) for a flyback converter (FC) working in continuous conduction mode (CCM). The union of fuzzy logic (FL) and adaptive neural networks (ANN) makes ANFIS more robust against model parameters’ uncertainties and perturbations in input voltage or load current. ANFIS inherits the advantages of structured knowledge representation from FL and learning capability from NN. Comparative analysis showed that the ANFIS controller offers not only the superior transient response characteristics, but also excellent steady-state characteristics compared to those of the FL controller (FLC) and proportional–integral–derivative (PID) controllers, thus validating its superiority over these traditional controllers. For this purpose, MATLAB/Simulink environment-based simulation results are presented for validation of the proposed converter compensated system under all operating conditions.
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Lutfy, O. F., Mohd S. B. Noor, M. H. Marhaban, and K. A. Abbas. "A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 223, no. 3 (December 18, 2008): 309–21. http://dx.doi.org/10.1243/09596518jsce683.

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Анотація:
This paper presents a genetically trained PID (proportional-integral-derivative)-like ANFIS (adaptive neuro-fuzzy inference system) acting as a feedback controller to control non-linear systems. Three important issues are addressed in this paper, which are, first, the evaluation of the ANFIS as a PID-like controller; second, the utilization of the GA (genetic algorithm) alone to train the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature; and, third, the determination of the input and output scaling factors for this controller by the GA. The GA, with real-coding operators, is used to adjust all of the ANFIS parameters, which include the input and output scaling factors, the centres and widths of the input membership functions (MFs), and the consequent parameters. To show the effectiveness of this controller and its learning method, several non-linear plants, including the CSTR (continuous stirred tank reactor), have been selected to be controlled by this controller through simulation. Moreover, this controller's robustness to output disturbances has also been tested and the results clearly indicated the remarkable performance of this controller and its learning algorithm. In addition, the result of comparing the performance of this controller with a genetically tuned classical PID controller has shown the superiority of the PID-like ANFIS controller.
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Більше джерел

Дисертації з теми "ANFIS CONTROLLER"

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Martins, Jos? Kleiton Ewerton da Costa. "An?lise de diferentes t?cnicas de controle na estrutura do ANFIS modificado." PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, 2017. https://repositorio.ufrn.br/jspui/handle/123456789/24224.

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Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES)
O trabalho faz uma an?lise de diferentes t?cnicas de controle na estrutura do ANFIS modificado, m?todo recente que se originou a partir de uma altera??o na estrutura do ANFIS, para realizar identifica??o e controle de plantas com ampla faixa de opera??o e n?o linearidade acentuada. O ANFIS modificado ? dividido em dois grandes est?gios, o primeiro sendo a identifica??o e o segundo o controle. Para realizar a identifica??o pode-se utilizar quaisquer t?cnicas. Nesse trabalho foram exploradas as t?cnicas de identifica??o de sistemas lineares mais conhecidas na literatura e o m?todo dos m?nimos quadrados. Assim como no est?gio da identifica??o, o est?gio de controle tamb?m permite utilizar quaisquer t?cnicas de projeto. Nesse trabalho foram exploradas as t?cnicas de sintonia de controladores PID mais conhecidas na literatura, na qual os controladores projetados foram incorporados na estrutura do ANFIS modificado para a obten??o de um controlador global n?o linear. Foi escolhido um sistema de tanques com multisse??es como estudo de caso e assim foi realizada a sua identifica??o atrav?s do ANFIS modificado, mostrando as qualidades do m?todo. Em seguida foi realizada uma compara??o de desempenho do ANFIS modificado utilizando os diferentes m?todos de sintonia e ao final chegando a uma metodologia sistem?tica para utiliza??o do ANFIS modificado como controlador global.
This work makes an analysis of different control techniques in the modified ANFIS structure, this method is recent and originated from a change in the ANFIS structure for perform identification and control of plants with wide operating range and accentuated non-linearity. The modified ANFIS is divided into two major stages, the first is the identification and the second is the control. In order to perform the identification, it is possible to use any techniques. In this work was explored the linear system identification more known in the literature and the least square estimation. As in the identification stage, the control stage can also use any techniques. This work the tuning of PID controllers will be explored, in which the designed controllers will be incorporated into the modified ANFIS structure to obtain a non-linear controller. A system of tanks with multisections was chosen as a case study and its identification through the modified ANFIS was performed, showing the qualities of the method. Then a performance comparison of the modified ANFIS will be performed using the different tuning methods and show a systematic methodology for use the modified ANFIS as global controller.
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2

Lazzari, Márcia Cristina. "Os anéis da serpente: dispositivos de controle e tecnologias de proteção." Pontifícia Universidade Católica de São Paulo, 2008. http://tede2.pucsp.br/handle/handle/2845.

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This work analyze the practices and the discourses of so-called Protection Network, defined as a group of institutions that confront the violations of the rights of children and young people, taking as parameter the Tutelary Councils (TC) and its association with different advisory body. Sustained by the power from the integration of public and private institutions, were mapped movements, and technologies of power disruption, analyzing information about the attendance provided to the community, by TCs in association with schools, and under supervision and guidance of the Law and the State. The analyses about the continuities and ruptures of the devices of attendance and protection of children and young people, raised approaches around the society of control announced by Deleuze, promoting a investigation about the regimes of disguised truth, found in institutional pathways. It is possible to map the practice of control through researches on the reports and documents relatives to the attendance provided by the CTs. The flows of power, present in the CTs, which manage the conflicts, prevent the access to data and scandalize the defense of rights, reaffirm the discourses of the government, put in movement the power and support the control all sectors related to children and young people. These are indications that participatory democracy favored ripples of catches of resistance and also, starts to acquire another meaning relative to the deterritorialization of space without jurisdiction. The questioning of the intolerable habits and actions reinforces the notion of inadequacy and isolation, and allows the review of the concentration camps, established under practice of snapshot control and police control, exercised by everybody
Neste trabalho são analisadas as práticas e os discursos da chamada Rede de Proteção, definida como o conjunto de instituições que compõem o enfrentamento às violações dos direitos das crianças e dos jovens, tendo como parâmetro os Conselhos Tutelares e suas articulações com outras instâncias. No interior de um fluxo de poderes emanados pela integração de instituições estatais e não estatais, são mapeados movimentos, rupturas e tecnologias de poder, examinando informações sobre atendimentos prestados à comunidade, pelos CTs em articulação com a escola, sob a supervisão e orientação da Lei e do Estado. As análises relativas às continuidades e rupturas dos dispositivos de atendimento e defesa de crianças e de jovens, suscitaram abordagens em torno da sociedade de controle anunciada por Deleuze, impulsionando a investigação dos regimes de verdade subjacentes, encontrados nas trajetórias institucionais. Tornou-se possível mapear práticas de controle por meio da pesquisa realizada junto aos relatórios e documentos relativos a atendimentos prestados. Os fluxos de controle, presentes nos CTs, que administram os conflitos, inviabilizam o acesso aos dados e alardeiam a defesa de direitos, reafirmam os discursos do governo, exercitam poderes e corroboram para a policialização de setores ligados às crianças e aos jovens. Tais elementos indicam que a democracia participativa favoreceu ondulações de capturas de resistências e também, passou a adquirir outro significado relativo à reterritorizaliação do espaço não jurisdicional. O questionamento de hábitos e ações insuportáveis reforça a noção de inadequação e isolamento, e permite a releitura do campo de concentração, instituído sob o exercício do controle instantâneo e policial exercido por todos
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3

Lima, Fábio. "Estimador neuro-fuzzy de velocidade aplicado ao controle vetorial sem sensores de motores de indução trifásicos." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-20092011-150232/.

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Анотація:
Este trabalho apresenta uma alternativa ao controle vetorial de motores de indução, sem a utilização de sensores para realimentação da velocidade mecânica do motor. Ao longo do tempo, diversas técnicas de controle vetorial têm sido propostas na literatura. Dentre elas está a técnica de controle por orientação de campo (FOC), muito utilizada na indústria e presente também neste trabalho. A principal desvantagem do FOC é a sua grande sensibilidade às variações paramétricas da máquina, as quais podem invalidar o modelo e as ações de controle. Nesse sentido, uma estimativa correta dos parâmetros da máquina, torna-se fundamental para o acionamento. Este trabalho propõe o desenvolvimento e implementação de um estimador baseado em um sistema de inferência neuro-fuzzy adaptativo (ANFIS) para o controle de velocidade do motor de indução trifásico em um acionamento sem sensores. Pelo fato do acionamento em malha fechada admitir diversas velocidades de regime estacionário para o motor, uma nova metodologia de treinamento por partição de frequência é proposta. Ainda, faz-se a validação do sistema utilizando a orientação de campo magnético no referencial de campo de entreferro da máquina. Simulações para avaliação do desempenho do estimador mediante o acionamento vetorial do motor foram realizadas utilizando o programa Matlab/Simulink. Para a validação prática do modelo, uma bancada de testes foi implementada; o acionamento do motor foi realizado por um inversor de frequência do tipo fonte de tensão (VSI) e o controle vetorial, incluindo o estimador neuro-fuzzy, foi realizado pelo pacote de tempo real do programa Matlab/Simulink, juntamente com uma placa de aquisição de dados da National Instruments.
This work presents an alternative sensorless vector control of induction motors. Several techniques for induction motor control have been proposed in the literature. Among these is the field oriented control (FOC), strongly used in industries and also in this work. The main drawback of the FOC technique is its sensibility to deviations of the parameters of the machine, which can deteriorate the control actions. Therefore, an accurate determination of the machines parameters is mandatory to the drive system. This work proposes the development of an adaptive neuro-fuzzy inference system (ANFIS) estimator to control the angular speed of a three-phase induction motor in a sensorless drive. In a closed loop configuration, several speed commands can be imposed to the motor. Thus, a new frequency partition training of ANFIS is proposed. Moreover, the ANFIS speed estimator is validated in a magnetizing flux oriented control scheme. Simulations to evaluate the performance of the estimator considering the vector drive system were done by the Matlab/Simulink. To determine the benefits of the proposed model a practical system was implemented using a voltage source inverter (VSI) and the vector control including the ANFIS estimator, carried out by the Real Time Toolbox from Matlab/Simulink and a data acquisition card from National Instruments.
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Rodrigues, Marconi C?mara. "T?cnicas inteligentes h?dridas para o controle de sistemas n?o lineares." Universidade Federal do Rio Grande do Norte, 2006. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15349.

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Анотація:
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Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior
A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics
Neste trabalho ? mostrado tanto o desenvolvimento quanto as caracter?sticas de algumas das principais t?cnicas utilizadas para o controle inteligente de sistemas. Partindo de um controlador fuzzy foi poss?vel aplicar t?cnicas de aprendizagem, similares ?s utilizadas pelas Redes Neurais Artificiais (RNA's), evoluir para os modelos neuro-fuzzy ANFIS e NEFCON. Estes modelos neuro-fuzzy foram aplicados a uma planta real do tipo ball and beam e tiveram tanto suas adapta??es quanto seus resultados comentados. Para cada controlador desenvolvido s?o especificadas as vari?veis de entrada, os par?metros utilizados para a adapta??o das vari?veis e os algoritmos aplicados em cada um deles. J? os resultados est?o voltados para a obten??o de um comparativo entre a fase inicial e a final da evolu??o dos controladores neuro-fuzzy, assim como, a aplicabilidade de cada um deles de acordo com suas caracter?sticas intr?nsecas
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Fonseca, Carlos Andr? Guerra. "Estrutura ANFIS modificada para identifica??o e controle de plantas com ampla faixa de opera??o e n?o linearidade acentuada." Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15222.

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In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method
Neste trabalho prop?e-se uma modifica??o na estrutura neurofuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) para a obten??o de um m?todo sistem?tico para identifica??o e controle de plantas com ampla faixa de opera??o e n?o linearidade acentuada, a partir de t?cnicas lineares de identifica??o e controle. Este m?todo se baseia na metodologia de m?ltiplos modelos. Dessa forma, obt?m-se modelos lineares locais e esses s?o combinados pela estrutura neurofuzzy proposta. Uma m?trica que permite combinar adequadamente esses modelos ? obtida ap?s o treinamento dessa estrutura, resultando na identifica??o global da planta. Para cada um desses modelos ? projetado um controlador. O controle global ? obtido a partir da combina??o dos sinais dos controladores locais. Essa mistura ? feita pelo ANFIS modificado. A modifica??o na arquitetura do ANFIS permite o compartilhamento do conhecimento adquirido pelo treinamento da estrutura empregada na combina??o de modelos locais. Assim n?o se faz necess?rio o treinamento da estrutura empregada na mistura de controladores. Avaliaram-se as estruturas modificadas atrav?s de dois estudos de caso. Verificou-se que ? poss?vel treinar apenas um ANFIS, para a obten??o de uma m?trica que permita a combina??o adequada dos modelos lineares, v?lidos localmente, e essa estrutura, j? ajustada, pode ser aplicada na combina??o de controladores lineares, projetados para cada um dos modelos, resultando em um sistema de controle que satisfaz as especifica??es de desempenho previamente estabelecidas. O m?todo proposto possibilita a utiliza??o de quaisquer t?cnicas de identifica??o e controle para a obten??o dos modelos e controladores locais, e a redu??o da complexidade de utiliza??o do ANFIS para identifica??o e controle. Neste trabalho priorizaram-se as t?cnicas mais simples de identifica??o e controle de sistemas de forma a simplificar a utiliza??o do m?todo
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Lopes, Jos? Soares Batista. "Estudo e implementa??o da t?cnica de intelig?ncia artificial para o controle de velocidade do motor-mancal com bobinado dividido utilizando o DSP TMS3208F28335." PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, 2016. https://repositorio.ufrn.br/jspui/handle/123456789/21802.

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Este trabalho descreve o estudo e a implementa??o digital embarcado em um DSP TMS 3208F28335 para o controle vetorial de velocidade do motor-mancal com bobinado dividido de 4 p?los com 250W de pot?ncia. As t?cnicas inteligentes: ANFIS e as Redes Neurais foram investigadas e implementadas computacionalmente para a avalia??o do desempenho do motor-mancal nas seguintes condi??es: operando como estimador de par?metros incertos, e como controlador de velocidade, respectivamente. Para isso, utilizou-se o programa MATLAB? e seu toolbox para as simula??es e os ajustes dos par?metros envolvendo a estrutura ANFIS, e tamb?m para as simula??es com a Rede Neural. Os resultados simulados mostraram um bom desempenho para as duas t?cnicas aplicadas, de forma diferente: como estimador, e como controlador de velocidade utilizando ambas um modelo do motor de indu??o operando como um motor-mancal. A parte experimental para o controle vetorial de velocidade utiliza tr?s malhas de controles: corrente, posi??o radial e velocidade, onde foram investigados a configura??o dos perif?ricos, as interfaces ou drivers para o acionamento do motor-mancal. Detalhes de configura??o dos perif?ricos do DSP TMS 3208F335 s?o descritas neste trabalho, assim como, as interfaces respons?veis pela aquisi??o da corrente, posi??o radial e velocidade do rotor. Por ?ltimo, s?o mostrados os resultados experimentas do motor-mancal comparando o funcionamento do controle vetorial cl?ssico com o controle neural.
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Miranda, Leonardo Cunha de. "Artefatos e linguagens de interação com sistemas digitais contemporâneos = os anéis interativos ajustáveis para a televisão digital interativa." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275786.

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Orientador: Maria Cecília Calani Baranauskas
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação
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Resumo: A digitalização da transmissão da televisão terrestre no Brasil e, consequentemente, a possibilidade de oferta de interatividade na televisão estabelece um novo paradigma de interação do telespectador com essa mídia com extremo potencial de impacto social, especialmente para a população brasileira. Entretanto, a existência de artefatos digitais comumente utilizados para a interação com o sistema de televisão hoje praticado não garante que esses dispositivos sejam os mais adequados aos avanços propostos com a Televisão Digital Interativa (TVDI). Além disso, a convivência de um número cada vez maior de equipamentos que fazem uso de controle remoto leva a interfaces mais complexas considerando os problemas existentes com o controle remoto já discutido na literatura por vários autores. O foco desta pesquisa de doutorado foi, portanto, investigar o design da interação nessa nova mídia com o objetivo de propor, desenvolver e validar novas formas de interação entre os usuários e a TVDI. Com base no entendimento de que uma interação mais direta com a TVDI passa pela necessidade de fazer com que o foco da interação se dirija mais à interface das aplicações interativas do que ao artefato físico de interação, chegamos a alguns resultados desta pesquisa. A tecnologia resultante desta pesquisa de doutorado saiu do plano das ideias, passando pelo seu projeto conceitual, de forma participativa, até sua implementação e validação junto a representantes do público-alvo. Podemos destacar algumas contribuições decorrentes da realização desta pesquisa no contexto dos artefatos físicos de interação com a TVDI: i) taxonomia para os artefatos físicos de interação; ii) recomendações de uso dos artefatos físicos de interação conhecidos na literatura; iii) análise sócio-técnica do domínio/contexto de novos artefatos físicos de interação; iv) diretrizes para novos artefatos físicos de interação; v) modelo de interação baseado em gestos via artefato físico de interação; vi) guidelines de design para novos artefatos físicos de interação; vii) especificações do design do produto e da linguagem de interação de um novo artefato digital para a TVDI; viii) implementações de protótipos de hardware e software do novo artefato digital para a TVDI; e ix) validação das especificações e dos protótipos do novo artefato digital para a TVDI junto ao público-alvo.
Abstract: The digitalization of terrestrial television broadcasting in Brazil and consequently the possibility of offering interactivity on television establish a new paradigm of interaction for the spectator with the media that has great potential to make a social impact, especially for the Brazilian population. However, the existence of digital artifacts commonly used to interact with current television system does not guarantee that those devices are adequate to the developments with the Interactive Digital Television (iDTV). Moreover, the coexistence of an increasing number of devices that make use of the remote control could result in more complex interfaces, considering the problems with remote control already discussed in the literature by several authors. The objective of this Ph.D. research was to investigate the interaction design in the iDTV with the purpose of proposing, developing and validating new ways of interaction with this new media. The research results are grounded in the understanding that a more direct interaction with iDTV involves making the focus of the interaction more on the interface of the interactive applications than on the physical artifact of interaction itself. The technology resulting from this research involved since its conceptual design, with a participatory approach, to its implementation and validation with real users from the target audience. Some contributions of this research in the context of physical artifacts of interaction with the iDTV can be highlighted: i) taxonomy for the physical artifacts of interaction; ii) use recommendations of physical artifacts of interaction known in the literature; iii) socio-technical analysis of the domain/context of new physical artifacts of interaction; iv) guidelines for new physical artifacts of interaction; v) gesture based interaction model via physical artifact of interaction; vi) design guidelines for new physical artifacts of interaction; vii) product design and interaction language specifications for new digital artifact for iDTV; viii) implementations of hardware and software prototypes for the new digital artifact for iDTV; and ix) validation of the specifications and prototypes of the new digital artifact for iDTV with the target audience.
Doutorado
Interação Humano-Computador
Doutor em Ciência da Computação
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Borges, Adroaldo Lazouriano Moreira. "Uma proposta de protocolo token ring sem fio." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-24032014-121359/.

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O protocolo Token Ring sem o (WTRP) é um protocolo distribuído de controle de acesso ao meio que provê qualidade de serviço em termos de uso de largura de banda e latência limitada. WTRP consiste de nós (estações) que formam topologicamente um anel. Contudo, quando o número de nós em um anel aumenta a latência aumenta e o tempo de reuso de token por parte de um nó em anel também aumenta. Neste trabalho, apresentamos uma versão extendida de WTRP com foco em reduzir a latência, tempo de reuso de token e permitir encaminhamento de dados entre anéis sem aumentar signicativamente o consumo de energia. Para provar o conceito que propomos, implementamos e testamos a nossa versão de WTRP usando simulador de rede - NS.
Wireless Token Ring Protocol (WTRP) is a distributed Medium Access Control protocol that provides quality of service in terms of reserved bandwidth and limited latency]. It consists of nodes or stations structured in ring topology. However, when the number of nodes in a ring increases latency and time of a node reuse token increases. In this work, we present an extended version WTRP that focus on reducing latency, time of token reuse and data forwarding among the rings in a MANet , without suggestive increasing of energy consumption. We have implemented and tested our version of WTRP in network simulator - NS.
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Dalecký, Štěpán. "Neuro-fuzzy systémy." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236066.

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The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being described and fuzzy logic is explained. The hybrid neuro-fuzzy system stemming from ANFIS system is designed on the basis of artificial neural networks, fuzzy sets and fuzzy logic. The upper-mentioned systems' functionality has been demonstrated on an inverted pendulum controlling problem. The three controllers have been designed for the controlling needs - the first one is on the basis of artificial neural networks, the second is a fuzzy one, and the third is based on ANFIS system.  The thesis is aimed at comparing the described systems, which the controllers have been designed on the basis of, and evaluating the hybrid neuro-fuzzy system ANFIS contribution in comparison with particular theory solutions. Finally, some experiments with the systems are demonstrated and findings are assessed.
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Tsung-YangLin and 林琮暘. "Design of H∞ ANFIS-Based Fuzzy Sliding Mode Controller." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/31140767950787712257.

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碩士
國立成功大學
系統及船舶機電工程學系
103
In practical, most of physical systems are nonlinear, and the feedback linearization method may be utilized to control the system. However, the system uncertainties and disturbances will affect the feasibility of the controller and make the closed-loop system hard to match the desired performance. To solve this problem, in this thesis, the ANFIS-based H_∞ Fuzzy Sliding Mode Controller is derived to form the proposed robust controller and to meet the pre-specified specifications. The proposed controller is composed of two control components. One component is the feedback-linearization based sliding mode controller, in which the control gains and the observer gains are optimally chosen from the standard H_∞ control problem. The other component is the fuzzy-based controller, whose membership functions are optimally tuned by the Adaptive-Network Based Fuzzy Inference System (ANFIS). With the proposed controller, the system tracking errors will be forced to the sliding surface by the first component. To ensure the achievement of tracking performance and desired specifications, the errors resulted from system uncertainties will be eliminated by the second component. The closed-loop system stability of the proposed controller is proved by the Lyapunov’s stability criterion. The largest allowable scale of uncertainties is then explored by an inequality proposed in this research. Finally, a robot manipulator with uncertainties is simulated to prove the feasibilities of the proposed composite controller.
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Книги з теми "ANFIS CONTROLLER"

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Seminário Proteção Radiológica e Controle Ambiental (1988 Belo Horizonte, Brazil). Seminário Proteção Radiológica e Controle Ambiental: [anais]. [Belo Horizonte]: Centro de Desenvolvimento da Tecnologia Nuclear, Empresas Nucleares Brasileiras, 1988.

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Simpósio, Nacional de Controle de Erosão (4th 1987 Marília Brazil). Controle de erosão: 4o. Simpósio Nacional de Controle de Erosão, 15 a 19 fev. 87, Marília, SP : anais. São Paulo, SP: Departamento de Aguas e Energia Elétrica, Centro Tecnológico de Hidráulica, 1987.

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Rede Nacional Feminista de Saúde (Brazil), ed. A presença da mulher no controle social das políticas de saúde: Anais da Capacitação de multiplicadoras em controle social das políticas de saúde. Belo Horizonte, MG: Mazza Edições, 2003.

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Simpósio EPUSP sobre Automação e Controle de Processos (1990 Cubatão, São Paulo, Brazil). Simpósio EPUSP sobre Automação e Controle de Processos--SEACOP, Cubatão, 12 e 13 de setembro de 1990: Anais. [São Paulo]: O Núcleo, 1990.

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Jornada Brasileira de Controle Interno (5th 2003 Rio de Janeiro, Brazil). Anais da V Jornada Brasileira de Controle Interno: 9 a 12 de dezembro de 2003, Rio de Janeiro, RJ. Rio de Janeiro, RJ: Prefeitura, Controladoria Geral, 2004.

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Jornada Brasileira de Controle Interno (5th 2003 Rio de Janeiro, Brazil). Anais da V Jornada Brasileira de Controle Interno: 9 a 12 de dezembro de 2003, Rio de Janeiro, RJ. Rio de Janeiro, RJ: Prefeitura, Controladoria Geral, 2004.

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Conferência, Estadual de Saúde de Mato Grosso (4th 2000 Cuiabá Mato Grosso Brazil). Anais da IV Conferência Estadual de Saúde de Mato Grosso: Efetivando o SUS: acesso, qualidade e humanização da atenção à saúde com controle social : I Mostra Estadual de Saúde da Família. Cuiabá, MT: Secretaria de Estado de Saúde de Mato Grosso, 2002.

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Rede Nacional Feminista de Sa Ude. A Presenca Da Mulher No Controle Social Das Politicas de Saude: Anais Da Capacitac~ao de Multiplicadoras Em Controle Social Das Politicas de Saude. Mazza Edic~oes, 2003.

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Fontes, Francisco Lucas de Lima, and Mayara Macêdo Melo. ANAIS DO II CONGRESSO ON-LINE NACIONAL DE CIÊNCIAS & SAÚDE (II CONCS). Literacia Cientifica Editora & Cursos, 2022. http://dx.doi.org/10.53524/lit.edt.978-65-84528-09-3.

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Em sua segunda edição, o Congresso On-line Nacional de Ciências & Saúde (CONCS), promovido pela Literacia Científica Editora & Cursos veio com um tema que envolveu Estado e Sociedade na busca pelo fortalecimento do SUS: ” Políticas públicas, democracia e direito à saúde: a multidisciplinaridade como meio para fortalecimento do SUS” . O objetivo do II CONCS foi promover discussão sobre direito à saúde; legislação do SUS; preceitos históricos para construção do SUS; participação, representação, controle social na gestão do SUS; desafios e perspectivas do SUS na atualidade; judicialização em saúde; ética e bioética na saúde; democracia e saúde; políticas públicas de saúde; integralidade, universalidade e equidade nas práticas assistenciais; descentralização, hierarquização e regionalização na organização do SUS; práticas multiprofissionais; educação em saúde; vigilância em saúde (epidemiológica, ambiental, sanitária e saúde do trabalhador); determinantes sociais em saúde; entre outras temáticas transversais que provocassem reflexão ao se pautar o tema central do evento em 2022. Realizado de 22 a 24 de abril de 2022, o evento foi realizado de maneira remota e contou com a participação de renomados especialistas das Ciências da Saúde e de outras áreas, garantindo a multidisciplinaridade e construção de conhecimentos nos três dias de evento. O II CONCS incluiu palestras, mesas redondas, minicursos, submissão de resumos, publicação dos resumos em anais pela Literacia Científica Editora & Cursos, além das certificações de participação no evento e minicurso e apresentação dos trabalhos.
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5a EXPOEPI Mostra Nacional de Experiências Bem-Sucedidas em Epidemiologia, Prevenção e Controle de Doenças, Brasília, DF, 4 a 6 de dezembro de 2005: Anais. Brasília, DF: Ministério da Saúde, Secretaria de Vigilância em Saúde, 2005.

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Частини книг з теми "ANFIS CONTROLLER"

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Bui, Van-Tri, and Dinh-Nhon Truong. "Improvement of ANFIS Controller for SVC Using PSO." In Advances in Intelligent Systems and Computing, 293–302. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62324-1_25.

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Hadhiq Khan, Shoeb Hussain, and Mohammad Abid Bazaz. "ANFIS Based Speed Controller for a Direct Torque Controlled Induction Motor Drive." In Advances in Intelligent Systems and Computing, 891–902. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47952-1_71.

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Dixit, Tata Venkat, Anamika Yadav, S. Gupta, and Almoataz Y. Abdelaziz. "Power Extraction from PV Module Using Hybrid ANFIS Controller." In Power Systems, 209–32. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6151-7_10.

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Shanmugasundaram, R., C. Ganesh, A. Singaravelan, B. Gunapriya, and B. Adhavan. "High-Performance ANFIS-Based Controller for BLDC Motor Drive." In Smart Innovation, Systems and Technologies, 435–49. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3675-2_33.

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Rachananjali, K., K. Bala Krishna, S. Suman, and V. Tejasree. "Modeling of an ANFIS Controller for Series–Parallel Hybrid Vehicle." In Advances in Intelligent Systems and Computing, 631–43. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7868-2_60.

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Ponce, Pedro, Arturo Molina, Israel Cayetano, Jose Gallardo, Hugo Salcedo, Jose Rodriguez, and Isela Carrera. "Fuzzy Logic Sugeno Controller Type-2 For Quadrotors Based on Anfis." In Nature-Inspired Computing for Control Systems, 195–230. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26230-7_8.

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Kumar, Abhishek, and R. Mitra. "Design of ANFIS Controller Based on Fusion Function for Linear Inverted Pendulum." In Advances in Intelligent Systems and Computing, 379–86. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-0740-5_45.

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Sree Varshini, G. Y., S. Charles Raja, and P. Venkatesh. "Design of ANFIS Controller for Power System Stability Enhancement Using FACTS Device." In Lecture Notes in Electrical Engineering, 1163–71. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2119-7_113.

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Manjusree, Y., and A. V. V. Sudhakar. "An Intelligent ANFIS Controller based PV Custom Device to enhance Power Quality." In Data Engineering and Communication Technology, 101–12. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0081-4_11.

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Mohanty, Asit, Meera Viswavandya, Sthitapragyan Mohanty, and Pragyan Paramita. "ANFIS-Based Controller for DFIG-Based Tidal Current Turbine to Improve System Stability." In Lecture Notes in Electrical Engineering, 115–22. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3589-7_12.

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Тези доповідей конференцій з теми "ANFIS CONTROLLER"

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Ting, Wang, and Xu Bo. "ANFIS Controller for Spacecraft Formation Flying." In 4th Annual International Conference on Computer Science Education: Innovation and Technology (CSEIT 2013). Global Science and Technology Forum, 2013. http://dx.doi.org/10.5176/2251-2195_cseit13.25.

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Sheng Qiang, Qing Zhou, X. Z. Gao, and Shuanghe Yu. "ANFIS controller for double inverted pendulum." In 2008 6th IEEE International Conference on Industrial Informatics (INDIN). IEEE, 2008. http://dx.doi.org/10.1109/indin.2008.4618147.

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Ginarsa, I. M., A. Soeprijanto, and M. H. Purnomo. "Controlling chaos using ANFIS-based Composite Controller (ANFIS-CC) in power systems." In 2009 International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME). IEEE, 2009. http://dx.doi.org/10.1109/icici-bme.2009.5417262.

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Saware, Abhishek, Navdeep Gavkar, Shubham Shinde, and Priyanka Kulkarni. "Performance Improvement of PID Controller for PMSM Using ANFIS Controller." In 2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP). IEEE, 2022. http://dx.doi.org/10.1109/iciccsp53532.2022.9862372.

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Shieh, Ming-Yuan, Ke-Hao Chang, Chen-Yang Chuang, Juing-Shian Chiou, and Jeng-Han Li. "ANFIS based Controller Design for Biped Robots." In Mechatronics, 2007 IEEE International Conference on. IEEE, 2007. http://dx.doi.org/10.1109/icmech.2007.4280017.

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Alasem, Rafe, Alamgir Hossain, Irfan Awan, and Hussein Mansour. "ANFIS Based AQM Controller for Congestion Control." In 2009 International Conference on Advanced Information Networking and Applications. IEEE, 2009. http://dx.doi.org/10.1109/aina.2009.125.

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Araghi, Sahar, Abbas Khosravi, and Douglas Creighton. "ANFIS Traffic Signal Controller for an Isolated Intersection." In International Conference on Fuzzy Computation Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0005135001750180.

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Shahri, Ali Reza Mohammad, Hamed Khoshravan, and Ahmad Naebi. "Designing Ping-Pong Player Robot Controller with ANFIS." In 2011 Third International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM). IEEE, 2011. http://dx.doi.org/10.1109/cimsim.2011.37.

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Hosen, Mohammad Anwar, Abbas Khosravi, Saeid Nahavandi, and Lachlan Sinnott. "Prediction interval-based ANFIS controller for nonlinear processes." In 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016. http://dx.doi.org/10.1109/ijcnn.2016.7727844.

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Nguyen, Duc Hien, Michel Joël Tchatchueng Kammegne, Ruxandra M. Botez, and Lucian Grigorie. "Open loop morphing wing architecture based ANFIS controller." In 16th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-4368.

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