Relevant bibliographies by topics / Fuzzy PI

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Fuzzy PI'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Fuzzy PI"

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Alharbi, Fahd. "Fuzzy PI Controller for RPR Networks." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (2019): 751–58. http://dx.doi.org/10.5373/jardcs/v11/20192629.

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Meziane, Khaddouj Ben, Faiza Dib, Nabil Benaya, and Ismail Boumhidi. "Optimized fuzzy PI controller for variable speed wind turbine using DE algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 14, no. 3 (2023): 1684. http://dx.doi.org/10.11591/ijpeds.v14.i3.pp1684-1693.

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To design an optimal fuzzy proportional-integral (PI) controller for the variable speed wind turbine systems, a new differential evolution (DE) algorithm approach is developed in this paper. We have investigated a fuzzy PI controller, in which fuzzy rules are applied to adapt the parameters of the PI controller founded on the error and its first-time derivative. The fuzzy PI controller's inputs and outputs are tuned using the DE optimization method. The superiority of the suggested (DE fuzzy PI) controller has been proved by comparing the results with (fuzzy PI) and only the PI controller appl
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Khaddouj, Ben Meziane, Dib Faiza, Benaya Nabil, and Boumhidi Ismail. "Optimized fuzzy PI controller for variable speed wind turbine using DE algorithm." International Journal of Power Electronics and Drive Systems 14, no. 3 (2023): 1684~1693. https://doi.org/10.11591/ijpeds.v14.i3.pp1684-1693.

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To design an optimal fuzzy proportional-integral (PI) controller for the variable speed wind turbine systems, a new differential evolution (DE) algorithm approach is developed in this paper. We have investigated a fuzzy PI controller, in which fuzzy rules are applied to adapt the parameters of the PI controller founded on the error and its first-time derivative. The fuzzy PI controller's inputs and outputs are tuned using the DE optimization method. The superiority of the suggested (DE fuzzy PI) controller has been proved by comparing the results with (fuzzy PI) and only the PI controller
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Zhang, Weixuan, Yu Fang, Rong Ye, and Zhengqun Wang. "Analysis and Design of a Double Fuzzy PI Controller of a Voltage Outer Loop in a Reversible Three-Phase PWM Converter." Energies 13, no. 15 (2020): 3778. http://dx.doi.org/10.3390/en13153778.

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Aiming at the application of a reversible three-phase pulse width modulation (PWM) converter with a wide range of AC side voltage and DC side voltage, a double fuzzy proportional integral (PI) controller for voltage outer loop was proposed. The structures of the proposed controller were motivated by the problems that either the traditional PI controller or single fuzzy PI controller cannot achieve high performance in a wide range of AC and DC voltage conditions. The presented double fuzzy controller studied in this paper is a sub fuzzy controller in addition to the traditional fuzzy PI control
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Xu, Xue Jun, Yong Zhong Lin, Hong Yang Sun, Yi Gen Lu, and Tian Lv. "Modeling and Development of Copper Wire Annealing Fuzzy Control System Based on Temperature Detecting." Applied Mechanics and Materials 487 (January 2014): 587–90. http://dx.doi.org/10.4028/www.scientific.net/amm.487.587.

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Copper wire continuous annealing is a key process of the cable production line. The accuracy of the temperature control directly determines whether the quality of copper wire meets the requirements. In this paper, the fuzzy-PI compound controller was selected and the structure of the annealing temperature fuzzy-PI control system was designed based on temperature measurement. Through the simulation of traditional PI control system and the improved Fuzzy-PI control system, the results show that the Fuzzy-PI controller is better than traditional PI controller. It verifies the feasibility and effe
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Singh, Yaduvir, Darshan Singh, and Dalveer Kaur. "Performance Comparison of PI and Fuzzy-PI Logic Speed Control of Induction Motor." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, no. 3 (2013): 400–413. http://dx.doi.org/10.24297/ijct.v6i3.4464.

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Single-phase induction motors are also used extensively for smaller loads. Speed control of induction motor has beenimplemented using PI (Proportional-Integral) controller and Fuzzy PI controller in Simulink MATLAB. The results showthat induction motor Fuzzy-PI speed control method results in a quicker response with no overshoot than the conventional PI controller. The settling time of induction motor Fuzzy-PI speed is better than the conventional PI controller. The integral time of weighted absolute error (ITEA) performance criteria also shows that the induction motor Fuzzy-PI speed contro
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Gharieb, W., and M. A. Sheirah. "Fuzzy Retuning PI Controller." IFAC Proceedings Volumes 30, no. 6 (1997): 723–27. http://dx.doi.org/10.1016/s1474-6670(17)43451-3.

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Bouserhane, Ismail K., Abdeldjebar Hazzab, Abdelkrim Boucheta, Benyounes Mazari, and Rahli Mostefa. "Optimal Fuzzy Self-Tuning of PI Controller Using Genetic Algorithm for Induction Motor Speed Control." International Journal of Automation Technology 2, no. 2 (2008): 85–95. http://dx.doi.org/10.20965/ijat.2008.p0085.

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We present induction motor speed control using optimal PI controller fuzzy gain scheduling. To improve PI controller performance, we designed fuzzy PI controller gain tuning for indirect-field oriented IMspeed control using fuzzy rules on-line to adapt PI controller parameters based on error and its first time derivative. To overcome the major disadvantage of fuzzy logic control, i.e., the lack of design technique, we propose optimization of fuzzy logic tuning parameters using a genetic algorithm. Optimally designed fuzzy logic provides suitable PI controller gain to achieve the desired speed
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RISKITASARI, SEPTYANA, BUDHY SETIAWAN, RATNA IKA PUTRI, and WAHYU AULIA NURWICAKSANA. "Kontrol Fuzzy PI untuk Pengaturan Kecepatan Angin oleh Wind Generator 1.42 Hp pada Wind Tunnel." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 8, no. 2 (2020): 288. http://dx.doi.org/10.26760/elkomika.v8i2.288.

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ABSTRAKWind generator merupakan bagian terpenting dari pembuatan Wind tunnel, dimana fungsinya adalah sebagai sumber penghasil angin. Pada proses desain kontrol, tahap pertama adalah mengumpulkan data parameter empiris wind generator real menggunakan jenis motor induksi 1.42 hp pada wind tunnel. Pada penelitian ini dibuat simulasi pengontrolan kecepatan generator angin menggunakan metode kontrol fuzzy PI untuk meningkatkan hasil dari respon sistem kestabilan dengan titik setel 2 m/s hingga 10 m/s. Simulasi kontrol dilakukan dengan memanfaatkan jenis motor induksi yang sebanding dengan plant. H
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Baharudin, N. N., and S. M. Ayob. "Brushless DC Motor Speed Control Using Single Input Fuzzy PI Controller." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 4 (2018): 1952. http://dx.doi.org/10.11591/ijpeds.v9.i4.pp1952-1966.

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<span lang="EN-US">Brushless DC (BLDC) motor is more reliable than classic DC motor with higher efficiency. Commonly used conventional linear controller such as PI, PID and PD controller. FLC is considered a replacement to conventional controller due to advantages on non-linear system. Hybrid controller e.g Fuzzy PI controller is developed to cope with drawback of both controller. Simplification of FLC in previous study is the pioneer of the idea of proposed method. Single-Input Fuzzy PI Controller (SIFPIC) is a hybrid controller that combines advantages of linear PI controller and fuzzy
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Dissertations / Theses on the topic "Fuzzy PI"

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Ashraf, Ali Junaid. "DC Motor Speed Control via Fuzzy / Pole Placement / PI Controller." Thesis, Högskolan Dalarna, Elektroteknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-5514.

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This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulati
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Whiter, A. M. "Pi-fuzzy Logic (and its application to open-world inference)." Thesis, University of Bristol, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378779.

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Vieira, Felipe Bezerra. "Estudo comparativo entre controladores Fuzzy e PI para um sistema de tanque." Universidade Federal Rural do Semi-Árido, 2017. http://bdtd.ufersa.edu.br:80/tede/handle/tede/717.

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Submitted by Lara Oliveira (lara@ufersa.edu.br) on 2017-05-25T21:49:55Z No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-05-26T11:53:21Z (GMT) No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-05-26T11:54:17Z (GMT) No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8
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Azcue, Puma José Luis 1981. "Controle direto de torque do motor de indução trifásico usando controlador Fuzzy tipo PI autoajustável." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258996.

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Orientador: Ernesto Ruppert Filho<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-16T21:19:34Z (GMT). No. of bitstreams: 1 AzcuePuma_JoseLuis_M.pdf: 8979349 bytes, checksum: a4b6502489a503823c332031a587452b (MD5) Previous issue date: 2010<br>Resumo: Neste trabalho apresenta-se o desempenho de um controlador fuzzy tipo PI autoajustável (FPIA) para o uso no esquema de controle direto de torque com modulação por vetores espaciais apresentado por J. Rodriguez e outros em 2004. Apresenta-se tamb
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Manoel, Filho Francisco 1974. "Projeto de um controlador fuzzy-PI para ajuste automático de velocidade da colhedora de cana de açúcar." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256779.

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Orientador: Nelson Luís Cappelli<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola<br>Made available in DSpace on 2018-08-23T21:10:32Z (GMT). No. of bitstreams: 1 ManoelFilho_Francisco_D.pdf: 3152234 bytes, checksum: ee75d133cc1ae9127b6dc69d40671dc7 (MD5) Previous issue date: 2013<br>Resumo: A mecanização da colheita de cana é um processo irreversível no Brasil, tanto por aspectos ambientais quanto econômicos. A agroindústria canavieira da Região Sudeste tem o maior índice de mecanização, compondo a maior frota de colhedoras de cana picada do país. Ess
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Biazeto, Anderson Ross. "Controladores de movimento da articulação do joelho de paraplégico com PI, PID e Fuzzy Takagi-Sugeno." Universidade Estadual de Londrina. Centro de Tecnologia e Urbanismo. Programa de Pós-Graduação em Engenharia Elétrica, 2015. http://www.bibliotecadigital.uel.br/document/?code=vtls000204157.

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A aplicação dos estímulos elétricos funcionais (EEF) (FES ? acrônico do inglês functional eletrical stimulation) em pacientes paraplégicos tem a função de reabilitação do tônus muscular e do movimento do membro afetado. Nos testes em laboratório com a aplicação dos estímulos, foram utilizados um eletroestimulador de oito canais e uma plataforma de teste, composta de uma cadeira ergonométrica para acomodação do participante, e uma barra de instrumentação composta por acelerômetros, giroscópios e eletrogoniômetro. A plataforma de testes é interligada ao software Matlab, sendo capaz de supervisão
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Jenkinas, Pavelas. "Intelektinės tiesiaeigės pavaros tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110617_190528-73617.

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Baigiamojo magistro darbo tiriamasis objektas – intelektinė tiesiaeigė elektros pavara. Tyrimo tikslas – ištirti tiesiaeigę elektros pavarą, valdoma neraiškiuoju reguliatoriumi. Uždaviniai – sudaryti intelektinės tiesiaeigės pavaros kompiuterinį modelį gauti ir ištirti imitacijos rezultatus, juos palyginti su tokia pačia PI reguliatoriumi valdoma pavara. Literatūros analizės dalyje išnagrinėtas neraiškiosios logikos panaudojimas valdant elektros pavaras. Pateikiami straipsniai, kuriose aprašomos elektros pavarų valdymo galimybės panaudojant neraiškiosios logikos reguliatorius. Teorinėje dalyje
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Ccantuta, Chirapo Karlos Alexander. "Controle de potência do gerador de relutância variável de 12/8 utilizando o controlador fuzzy pi auto-ajustável." reponame:Repositório Institucional da UFABC, 2018.

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Orientador: Prof. Dr. José Luis Azcue Puma<br>Coorientador: Prof. Dr. José Alberto Torrico Altuna<br>Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, Santo André, 2018.<br>Este trabalho apresenta o controle de potência do gerador de relutância variável de 12/8 utilizando o controlador Fuzzy PI auto-ajustável e o controlador P+ressonante para o conversor conectado à rede elétrica. Inicialmente são estudados os princípios de operação da máquina e a topologia do conversor eletrônico de potência. Usando o software de simulação Matlab/Simulink
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Catata, Elmer Osman Hancco. "Controlador PI FUZZY aplicado ao controle direto de potência do gerador de relutância variável de 12/8 conectado à rede elétrica." reponame:Repositório Institucional da UFABC, 2016.

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Orientador: Prof. Dr. José Luis Azcue Puma<br>Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2016.<br>Este trabalho apresenta o controle direto de potencia do gerador de relutancia variavel de 12/8 utilizando o controlador fuzzy PI auto-ajustavel e o controle vetorial do inversor conectado à rede eletrica. Inicialmente são estudados os principios de operação da maquina e a topologia do conversor eletronico de potencia que sera utilizado para aciona-lo. Usando o software de simulaçãoMatlab/Simulink é implementado o modelo da maquina de r
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Silva, de Amorim Priscila. "Aplicação de inteligência artificial no controle e automação de sistemas de ar comprimido com foco na eficiência energética." Universidade Federal de Pernambuco, 2010. https://repositorio.ufpe.br/handle/123456789/5110.

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Made available in DSpace on 2014-06-12T17:36:12Z (GMT). No. of bitstreams: 2 arquivo2555_1.pdf: 2355246 bytes, checksum: 67878edb28caadb5dda261416c723874 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010<br>Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>Do total de energia consumida no país, aproximadamente 43% é consumida pelo setor industrial e do total da energia elétrica consumida na indústria, cerca de 60% destinase aos motores elétricos. Depois da energia elétrica, o ar comprimido é a forma de energia mais con
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Book chapters on the topic "Fuzzy PI"

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Norris, Donald J. "Fuzzy Logic System." In Beginning Artificial Intelligence with the Raspberry Pi. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2743-5_5.

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Luna-Lobano, Leticia, Prometeo Cortés-Antonio, Oscar Castillo, and Patricia Melin. "Analysis of P, PI, Fuzzy and Fuzzy PI Controllers for Control Position in Omnidirectional Robots." In Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35445-9_26.

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Tanaka, Kazuo, and Manabu Sano. "Parameter Adjustment Laws of Fuzzy Pi Controllers for First Order Lag Systems with Dead Time." In Fuzzy Logic. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2_49.

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Luna-Lobano, Leticia, Prometeo Cortés-Antonio, Oscar Castillo, and Patricia Melin. "Comparative Study of P, PI, Fuzzy and Fuzzy PI Controllers in Position Control for Omnidirectional Robots." In Advances in Soft Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33749-0_57.

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Denizci, Aykut, Sinan Karadeniz, and Cenk Ulu. "Fuzzy Cognitive Map Based PI Controller Design." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51156-2_146.

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Mendes, Nuno, Pedro Neto, J. Norberto Pires, and A. Paulo Moreira. "Fuzzy-PI Force Control for Industrial Robotics." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15810-0_41.

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Nguyen, Ngoc-Tung, and Hong-Hee Lee. "Fuzzy PI Controller for Grid-Connected Inverters." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25944-9_39.

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de Barros, Jean-Camille. "Benchmark Between Three Controllers in IFOC: PI, IP and New Fuzzy-PI Regulator." In Advances in Soft Computing. Springer London, 2003. http://dx.doi.org/10.1007/978-1-4471-3744-3_8.

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Pavankumar, B., and Saroj Pradhan. "Performance Analysis of Hybrid Filter Using PI and PI-Fuzzy Based UVTG Technique." In Computational Intelligence in Pattern Recognition. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3089-8_6.

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Labbadi, Moussa, Kamal Elyaalaoui, Loubna Bousselamti, Mohammed Ouassaid, and Mohamed Cherkaoui. "Primary Frequency Control for Wind Farm Using a Novel PI Fuzzy PI Controller." In Studies in Systems, Decision and Control. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98737-4_6.

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Conference papers on the topic "Fuzzy PI"

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Kumar, Indrajeet, Anand Singh, and Sonali R. Nandanwar. "Static Synchronous Compensator Using Fuzzy-PI Controller." In 2024 IEEE 2nd International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP). IEEE, 2024. https://doi.org/10.1109/ihcsp63227.2024.10960130.

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Kumar, Indrajeet, Anand Singh, and Sonali R. Nandanwar. "STATCOM Performance Analysis with a Fuzzy-PI Controller." In 2024 IEEE 2nd International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP). IEEE, 2024. https://doi.org/10.1109/ihcsp63227.2024.10960155.

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Salazar-Heise, Fernando, and Nelson Aros-Onate. "PI-FUZZY and PI Algorithm in MRAS." In 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA). IEEE, 2018. http://dx.doi.org/10.1109/ica-acca.2018.8609854.

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Boldyreff, Anton S., Vladimir V. Ignatyev, Andrey V. Kovalev, Oleg B. Spiridonov, Alexandra S. Ignatyeva, and Vladimir I. Bozhich. "Model of adaptive system of neuro-fuzzy inference based on pi- and pi-fuzzy-controllers." In Emerging Technologies, edited by Richard C. Hollins, Gerald S. Buller, and Robert A. Lamb. SPIE, 2018. http://dx.doi.org/10.1117/12.2513302.

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Nayeri, M. R., S. Khosravi, and M. Aliyari Sh. "Design and implementation double input fuzzy PI and fuzzy gain scheduling PI controller on hydraulic plant." In 2013 13th Iranian Conference on Fuzzy Systems (IFSC). IEEE, 2013. http://dx.doi.org/10.1109/ifsc.2013.6675648.

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Wang, Wei. "Fuzzy PI+Fuzzy ID Controller for PMSM Servo System." In 2011 Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2011. http://dx.doi.org/10.1109/appeec.2011.5749098.

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Ferreira, A. M. D. "Fuzzy power system stabilizer including a fuzzy PI controller." In UKACC International Conference on Control (CONTROL '98). IEE, 1998. http://dx.doi.org/10.1049/cp:19980342.

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Kim, Jongkyoo, Ok-Kyu Choi, Hyosin Kim, and Jin S. Lee. "Asymptotic stability analysis of TSK fuzzy PI control system using circle criterion." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337816.

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Nie, Maowen, and Woei Wan Tan. "Derivation of the analytical structure of symmetrical IT2 fuzzy PD and PI controllers." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584078.

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Du, Wentao, Jingyu Zhu, Zhenyu Wang, Chao Wang, Heming Geng, and Kun Liu. "Design And Bench Verification of PSO-Optimized Fuzzy PI Control Strategy for PMSM Based on UAV Flight Load Simulation." In SAE 2024 Vehicle Powertrain Diversification Technology Forum. SAE International, 2025. https://doi.org/10.4271/2025-01-7049.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The development of the electrification technology of unmanned aerial vehicle (UAV) puts forward higher requirements for the control performance and verification methods of permanent magnet synchronous motor (PMSM). In this paper, a fuzzy PI control strategy based on a particle swarm optimization (PSO) algorithm is proposed to optimize the parameters of the PI controller and improve the dynamic response and control accuracy of PMSM. Firstly, Matlab/Simulink is used to build an online vector control model of PMSM, and the
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