Relevant bibliographies by topics / ANFIS CONTROLLER

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Academic literature on the topic 'ANFIS CONTROLLER'

Author: Grafiati
Published: 11 September 2023
Last updated: 22 June 2025

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Journal articles on the topic "ANFIS CONTROLLER"

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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 (2016): 1750034. http://dx.doi.org/10.1142/s0218126617500347.

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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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Baz, Rachida, Khalid El Majdoub, Fouad Giri, and Ossama Ammari. "Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 745. http://dx.doi.org/10.11591/ijeecs.v34.i2.pp745-755.

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Electric vehicles (EVs) have gained importance in recent years, prompting the development of several control systems to improve their efficiency and performance. In this work, a quarter electric vehicle (QEV) was controlled using a conventional proportional integral derivative (PID) and fuzzy controller to examine and compare with the response of the adaptive neuro-fuzzy inference system (ANFIS) controller. The response of the ANFIS controller was evaluated using MATLAB/Simulink according to different parameters and compared with those of other controllers. In addition, the simulation was based on different driving conditions such as the acceleration and deceleration modes and the type of road: wet and dry. The simulations were carried out on a longitudinal electric vehicle model based on a brushless DC motor, including the Pacejka tire model. The results showed that the ANFIS controller outperformed the PID and fuzzy logic controllers, providing superior dynamic responsiveness and stability when the ANFIS controller smoothly followed the input speed and the longitudinal slip value reached 3%.
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Baz, Rachida, Khalid El Majdoub, Fouad Giri, and Ossama Ammari. "Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 745–55. https://doi.org/10.11591/ijeecs.v34.i2.pp745-755.

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Electric vehicles (EVs) have gained importance in recent years, prompting the development of several control systems to improve their efficiency and performance. In this work, a quarter electric vehicle (QEV) was controlled using a conventional proportional integral derivative (PID) and fuzzy controller to examine and compare with the response of the adaptive neuro-fuzzy inference system (ANFIS) controller. The response of the ANFIS controller was evaluated using MATLAB/Simulink according to different parameters and compared with those of other controllers. In addition, the simulation was based on different driving conditions such as the acceleration and deceleration modes and the type of road: wet and dry. The simulations were carried out on a longitudinal electric vehicle model based on a brushless DC motor, including the Pacejka tire model. The results showed that the ANFIS controller outperformed the PID and fuzzy logic controllers, providing superior dynamic responsiveness and stability when the ANFIS controller smoothly followed the input speed and the longitudinal slip value reached 3%.
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P, Sobha Rani, Padma R, Sarveswara Prasad R, and Rathnakar Kumar P. "Enhancement of power quality in grid connected PV system." Indian Journal of Science and Technology 13, no. 35 (2020): 3630–41. https://doi.org/10.17485/IJST/v13i35.1266.

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Abstract <strong>Background/Objectives:</strong>&nbsp;In grid connected photo voltaic systems inverter is the key element. The inverter is required to shape dc current into sinusoidal current and provide fast response under various disturbances. The quality of power injected into the grid depends on proper inverter control. The objective of this paper is reducing harmonics and to improve power factor in grid connected system with balanced and unbalanced loads.<strong>Methods/Statistical analysis:</strong>&nbsp;In this study, three control mechanisms, adaptive neuro fuzzy inference system (ANFIS), ANFIS with static synchronous compensator (STATCOM), ANFIS with dynamic voltage restorer (DVR) are employed to improve power quality. The performances of fuzzy and ANFIS controllers are compared in terms of total harmonic distortion and power factor. MATLAB/ Simulink is used to perform the simulation.&nbsp;<strong>Findings:</strong>&nbsp;ANFIS controller is more effective compared to fuzzy controller. ANFIS controller with DVR gives less THD and improved power factor as compared to fuzzy controller.<strong>Novelty/Applications:</strong>&nbsp;Fuzzy and neural network controllers do not need any mathematical modelling and give accurate control as compared to classical PI controllers. In this work, ANFIS controller alone and ANFIS controller along with custom power devices STATCOM and DVR are designed for reduction in total harmonic distortion and improved power factor. The results are tabulated, analyzed and compared with fuzzy controller. It has been shown that ANFIS controller gives better performance compared to fuzzy controller. <strong>Keywords:</strong> Artificial neural networks (ANN); Adaptive neuro fuzzy inference system (ANFIS); fuzzy controller; power factor; power quality; Total Harmonic Distortion (THD)
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Kheioon, Imad A., Raheem Al-Sabur, and Abdel-Nasser Sharkawy. "Design and Modeling of an Intelligent Robotic Gripper Using a Cam Mechanism with Position and Force Control Using an Adaptive Neuro-Fuzzy Computing Technique." Automation 6, no. 1 (2025): 4. https://doi.org/10.3390/automation6010004.

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Manufacturers increasingly turn to robotic gripper designs to improve the efficiency of gripping and moving objects and provide greater flexibility to these objects. Neuro-fuzzy techniques are the most widespread in developing gripper designs. In this study, the traditional gripper design is modified by adding a suitable cam that makes it compatible with the basic design, and an adaptive neuro-fuzzy inference system (ANFIS) is used in a MATLAB Simulink environment. The developed gripper investigates the follower path concerning the cam surface curve, and the gripper position is controlled using the developed ANFIS-PID. Three methods are examined in the developed ANFIS-PID controller: grid partitioning (genfis1), subtractive clustering (genfis2), and fuzzy C-means clustering (genfis3). The results show that the added cam can improve the gripping strength and that the ANFIS-PID model effectively handles the rise time and supported settling time. The developed ANFIS-PID controller demonstrates more efficient performance than Fuzzy-PID and traditional tuned-PID controllers. This proposed controller does not achieve any overshoot, and the rise time is improved by approximately 50–51%, and the steady-state error is improved by 75–95%, compared with Fuzzy-PID and tuned PID controllers. Moreover, the developed ANFIS-PID controller provides more stability for a wide range of set point displacements—0.05 cm, 0.5 cm, and 1.5 cm—during the testing period. The developed ANFIS-PID controller is not affected by disturbance, making it well suited for robotic gripper designs. Grip force control is also investigated using the proposed ANFIS-PID controller and compared with the Fuzzy-PID in three scenarios. The result from this force control proves objects’ higher actual gripping performance by using the proposed ANFIS-PID.
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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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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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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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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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Manku Priya. "Adaptive Control of Three-Level UPQC via ANFIS for Enhanced Power Quality: A MATLAB/Simulink-Based Evaluation." Journal of Electrical Systems 20, no. 11s (2024): 1150–65. https://doi.org/10.52783/jes.7393.

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This paper presents a comprehensive study of a three-level Unified Power Quality Conditioner (UPQC) controlled by Adaptive Neuro-Fuzzy Inference System (ANFIS) and its simulation in MATLAB/Simulink. The UPQC is designed to enhance power quality by simultaneously mitigating voltage sags, swells, and harmonic distortions while providing voltage regulation. The proposed ANFIS controller leverages the advantages of both fuzzy logic and neural networks, allowing for adaptive learning and improved performance in dynamic environments. Simulation results demonstrate the effectiveness of the ANFIS controller in comparison to traditional Proportional-Integral (PI) and fuzzy controllers. Key performance metrics, including response time, settling time, and steady-state error, are evaluated across various operating conditions. The findings indicate that the ANFIS-controlled UPQC outperforms both the PI and fuzzy controllers in terms of rapid response and robustness, making it a promising solution for advanced power quality management in modern electrical systems. This research contributes to the growing body of knowledge on intelligent control strategies for power quality enhancement, emphasizing the potential of ANFIS in improving the performance of UPQC systems.
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Rakhi, S. Ambhore, B. Mandake Yogesh, and S. Bankar Deepak. "Simulation and Analysis of Performance of SRM by Using Different Controller." Indian Journal of Science and Technology 16, no. 25 (2023): 1910–17. https://doi.org/10.17485/IJST/v16i25.1166.

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Abstract <strong>Objectives:</strong>&nbsp;With concerns about energy efficiency, Switched Reluctance Motors (SRM) have piqued the interest of researchers in the fields of Electric Vehicle (EV) due to their robust construction, fault-tolerant operation, high starting torque without the problem of excessive inrush current, and highspeed operation. The goal of this research is Simulation and Analysis of Performance of SRM by Using Different Controller that is fuzzy logic controllers.&nbsp;<strong>Methods:</strong>&nbsp;This study represents a new modified fuzzy-pi controller (MFPI) and Adaptive Neural Fuzzy Interference System (ANFIS) modelled on a high power Switched Reluctances Motor for applications. The simulation was carried out using MATLAB, the different parameters included speed control of SRM by ANFIS and FUZZY LOGIC and FUZZY PI Controller. The comparisons are carried out in terms of the Variation Without Controller, Variation With Fuzzy Logic Controller, Variation With Fuzzy Pi Controller and Variation With Anfis Controller.<strong>&nbsp;Findings:</strong>&nbsp;The motor speed was regulated by the standard fuzzy- PI (FPI) and ANFIS controller after designing a non-linear model of SRM. The fuzzy logic controller gives a perfect speed tracking without overshoot and enhances the speed regulation. Also, ANFIS is used in this model to control the speed regulation. From the result it can be concluded that the speed can regulate fast and accuracy by ANFIS. It was observed that the maximum torque obtained at 5s is 49N-m for Variation Without Controller. Current (For Three Phases) was found ith maximum variation at 8s is 17A in case of Variation With Anfis Controller. Initially speed with maximum value is 9100rpm and at 8s 6200rpm with oscillation only at starting in case of Variation With Anfis Controller.&nbsp;<strong>Novelty:</strong>&nbsp;This study presents a new approach that combines fuzzy logic, fuzzy PI, and ANFIS controllers for achieving optimum reference tracking for SRM drives. The use of these controllers improves speed regulation and offers accurate speed tracking without any overshoot. This approach is not commonly reported in the literature and represents a unique contribution to the field of SRM control. Additionally, the simulation results demonstratethe effectiveness of the proposed approach in achieving better speed control compared to state-of-the-art techniques. <strong>Keywords:</strong> Switched Reluctance Motor; Hysteresis Current Controller; Fuzzy Logic Controller; ANFIS Controller &amp; Torque Control
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Ghimire, Sajesan, Bhriguraj Bhattrai, Sulav Shrestha, and Sagar Poudel. "Comparative Assessment of PID and ANFIS Controllers in an Automatic Voltage Regulator." OODBODHAN 7 (December 31, 2024): 50–57. https://doi.org/10.3126/oodbodhan.v7i1.75766.

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This research paper provides an in-depth analysis of the performance characteristics of PID (Proportional-Integral-Derivative) and ANFIS (Adaptive Neuro-Fuzzy Inference System) controllers within Automatic Voltage Regulator (AVR) systems. The primary objective is to evaluate these controllers' behavior and efficacy, potentially extending their application to other control systems in the power sector. Utilizing the robust capabilities of MATLAB-SIMULINK, the PID controller was finely tuned, while the ANFIS controller was trained using carefully selected data. The findings highlight the ANFIS controller's exceptional performance, characterized by a notably fast settling time of 1.7277 seconds and 1.8716% overshoot. In comparison, the PID controller exhibited greater overshoot and a longer settling time, demonstrating less efficiency. These results were compared with other published research papers, further validating the superior performance of the ANFIS controller. This detailed evaluation confirms the ANFIS controller's superiority, offering significant guidance for researchers and industry professionals in making informed decisions regarding the optimal choice of controllers for various control systems.
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Dissertations / Theses on the topic "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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Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-11-01T21:47:48Z No. of bitstreams: 1 JoseKleitonEwertonDaCostaMartins_DISSERT.pdf: 3450112 bytes, checksum: 43beab3e6259be22eeed518fd67eaefc (MD5)<br>Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-11-08T21:43:16Z (GMT) No. of bitstreams: 1 JoseKleitonEwertonDaCostaMartins_DISSERT.pdf: 3450112 bytes, checksum: 43beab3e6259be22eeed518fd67eaefc (MD5)<br>Made available in DSpace on 2017-11-08T21:43:16Z (GMT). No. of bitstreams: 1 JoseKleitonEwertonDaCostaMartins_DISSERT.pdf: 3450112 bytes, checksum: 43beab3e6259be22eeed518fd67eaefc (MD5) Previous issue date: 2017-06-23<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES)<br>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.<br>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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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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Made available in DSpace on 2016-04-25T20:22:29Z (GMT). No. of bitstreams: 1 Marcia Cristina Lazzari.pdf: 1055866 bytes, checksum: 7e37be836bb85dd4fd0ae4f8dfcf4fae (MD5) Previous issue date: 2008-10-08<br>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<br>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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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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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.<br>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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Made available in DSpace on 2014-12-17T14:55:48Z (GMT). No. of bitstreams: 1 MarconiCR.pdf: 3477416 bytes, checksum: 7bf9d3b9014c2ba726d8694085022188 (MD5) Previous issue date: 2006-02-17<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>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<br>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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Made available in DSpace on 2014-12-17T14:55:11Z (GMT). No. of bitstreams: 1 CarlosAGF_TESE.pdf: 1739972 bytes, checksum: 7401db4e68ede642dc9d65e00bd935e6 (MD5) Previous issue date: 2012-12-21<br>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<br>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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Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-01-27T12:26:54Z No. of bitstreams: 1 JoseSoaresBatistaLopes_TESE.pdf: 3701361 bytes, checksum: 945caee9725d682534c235543f919e4b (MD5)<br>Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-01-30T13:07:29Z (GMT) No. of bitstreams: 1 JoseSoaresBatistaLopes_TESE.pdf: 3701361 bytes, checksum: 945caee9725d682534c235543f919e4b (MD5)<br>Made available in DSpace on 2017-01-30T13:07:29Z (GMT). No. of bitstreams: 1 JoseSoaresBatistaLopes_TESE.pdf: 3701361 bytes, checksum: 945caee9725d682534c235543f919e4b (MD5) Previous issue date: 2016-06-17<br>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<br>Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-16T23:18:27Z (GMT). No. of bitstreams: 1 Miranda_LeonardoCunhade_D.pdf: 4387805 bytes, checksum: b138e75ab0fe002567c99b3af4fd3a50 (MD5) Previous issue date: 2010<br>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.<br>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.<br>Doutorado<br>Interação Humano-Computador<br>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.<br>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<br>國立成功大學<br>系統及船舶機電工程學系<br>103<br>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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Books on the topic "ANFIS CONTROLLER"

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Seminário Proteção Radiológica e Controle Ambiental (1988 Belo Horizonte, Brazil). Seminário Proteção Radiológica e Controle Ambiental: [anais]. 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. 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. 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. 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. 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. 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. 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 &amp; Saúde (CONCS), promovido pela Literacia Científica Editora &amp; 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 &amp; 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. Ministério da Saúde, Secretaria de Vigilância em Saúde, 2005.

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Book chapters on the topic "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. 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. 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. 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. 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. 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, et al. "Fuzzy Logic Sugeno Controller Type-2 For Quadrotors Based on Anfis." In Nature-Inspired Computing for Control Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26230-7_8.

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Gandham, Naga Venkata Karthik, and Pragaspathy Subramani. "Performance Evaluation of Off Grid Hybrid Distribution System with ANFIS Controller." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-48891-7_1.

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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. 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. 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. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0081-4_11.

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Conference papers on the topic "ANFIS CONTROLLER"

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Mohapatra, Sayaprasad, Lalit Mohan Satapathy, Sanjeeb Kumar Kar, Narayan Nahak, Manoj Kumar Debnath, and Akshaya Kumar Patra. "Design and Analysis of ANFIS Controller based Photovoltaic System." In 2024 3rd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON). IEEE, 2024. https://doi.org/10.1109/odicon62106.2024.10797526.

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Azis, Satria Muhammad, Oyas Wahyunggoro, and Adha Imam Cahyadi. "Speed Control of Coconut Grater Machine using PID based ANFIS Controller." In 2024 16th International Conference on Information Technology and Electrical Engineering (ICITEE). IEEE, 2024. https://doi.org/10.1109/icitee62483.2024.10808334.

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Siddula, Sundeep, Vallala Yashwanth, Bhavani Vadlakonda, Chaithanya Kumar Vungarala, and Raju Pathi. "Enhancing Electric Vehicle Efficiency through an ANFIS Controller-Driven Energy Management System." In 2024 4th International Conference on Intelligent Technologies (CONIT). IEEE, 2024. http://dx.doi.org/10.1109/conit61985.2024.10626729.

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Siddula, Sundeep, Vallala Yashwanth, Bhavani Vadlakonda, Chaithanya Kumar Vungarala, and Raju Pathi. "Optimizing Electric Vehicle Efficiency-The Role of ANFIS Controller-Driven Energy Management." In 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2024. http://dx.doi.org/10.1109/icpeices62430.2024.10719253.

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Halder, Kaushik, and M. Felix Orlando. "Trajectory Tracking Controller Design for a Ball-Plate Balancing System Using ANFIS." In 2024 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). IEEE, 2024. https://doi.org/10.1109/pedes61459.2024.10961904.

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6

Kharola, Ashwani, Ritvik Dobriyal, Rakesh Chandmal Sharma, Neeraj Sharma, Ashwini Sharma, and Anuj Raturi. "Hydrodynamic Flow Characteristics Prediction for Bluff Body Wake via Novel Adaptive Neuro-Fuzzy Controller Avoiding Fuzzy Rule Explosion." In Automotive Technical Papers. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-5081.

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Abstract:
&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This study analyses the effect of Reynolds number (&lt;i&gt;Re&lt;/i&gt;) and bluff body shape (quantified by shape factor &lt;i&gt;SF&lt;/i&gt;) variation on various hydrodynamic characteristics of unsteady bluff body flow, such as Strouhal number, maximum lift coefficient, and mean drag coefficient. The study initially examines a relationship among these characteristics and further utilizes artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) controllers for their precise prediction. The results from real-time computational fluid dynamics (CFD) experimentations were gathered and considered to train ANN controllers. A novel ANFIS controller has been designed using only three membership functions thus solving the problem of fuzzy rule explosion. The results indicate that both the ANN and ANFIS controllers can precisely predict these hydrodynamic flow characteristics as validated through minimal values of root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). It is observed that ANFIS controller provides better results compared to the proposed feed-forward ANN controller. The RMSE, MAE, and MAPE obtained for ANFIS model for different shape factors for maximum lift coefficient were 0.0024, 0.002, and 0.85%, respectively.&lt;/div&gt;&lt;/div&gt;
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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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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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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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