Relevant bibliographies by topics / Takagi-Sugeno modeling

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

Academic literature on the topic 'Takagi-Sugeno modeling'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Takagi-Sugeno modeling"

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Männle, Manfred. "FTSM — Fast Takagi-Sugeno Fuzzy Modeling." IFAC Proceedings Volumes 33, no. 11 (2000): 651–56. http://dx.doi.org/10.1016/s1474-6670(17)37434-7.

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Shao, Xuejuan, Jinggang Zhang, Xueliang Zhang, Zhicheng Zhao, and Zhimei Chen. "A novel anti-swing and position control method for overhead crane." Science Progress 103, no. 1 (2019): 003685041988353. http://dx.doi.org/10.1177/0036850419883539.

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Based on Takagi–Sugeno fuzzy modeling and linear matrix inequality with decay rate, this article presents a novel anti-swing and position control scheme for overhead cranes. First, the simplified nonlinear dynamic model is proposed by adopting a virtual control variable method to reduce the number of nonlinear terms. Then, the Takagi–Sugeno fuzzy model is constructed using sector nonlinear technique, and the anti-swing and position controller of overhead crane is designed based on a linear matrix inequality with decay rate. Finally, the proposed control method is compared with the traditional
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Sriraman, R., R. Samidurai, V. C. Amritha, G. Rachakit, and Prasanalakshmi Balaji. "System decomposition-based stability criteria for Takagi-Sugeno fuzzy uncertain stochastic delayed neural networks in quaternion field." AIMS Mathematics 8, no. 5 (2023): 11589–616. http://dx.doi.org/10.3934/math.2023587.

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<abstract><p>Stochastic disturbances often occur in real-world systems which can lead to undesirable system dynamics. Therefore, it is necessary to investigate stochastic disturbances in neural network modeling. As such, this paper examines the stability problem for Takagi-Sugeno fuzzy uncertain quaternion-valued stochastic neural networks. By applying Takagi-Sugeno fuzzy models and stochastic analysis, we first consider a general form of Takagi-Sugeno fuzzy uncertain quaternion-valued stochastic neural networks with time-varying delays. Then, by constructing suitable Lyapunov-Kras
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Keshwani, Deepak R., David D. Jones, and Rhonda M. Brand. "Review: Takagi–Sugeno Fuzzy Modeling of Skin Permeability." Cutaneous and Ocular Toxicology 24, no. 3 (2005): 149–63. http://dx.doi.org/10.1080/15569520500278690.

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Hadjili, M. L., and V. Wertz. "Takagi-Sugeno fuzzy modeling incorporating input variables selection." IEEE Transactions on Fuzzy Systems 10, no. 6 (2002): 728–42. http://dx.doi.org/10.1109/tfuzz.2002.805897.

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Salgado, Catia M., Joaquim L. Viegas, Carlos S. Azevedo, Marta C. Ferreira, Susana M. Vieira, and Joao M. C. Sousa. "Takagi–Sugeno Fuzzy Modeling Using Mixed Fuzzy Clustering." IEEE Transactions on Fuzzy Systems 25, no. 6 (2017): 1417–29. http://dx.doi.org/10.1109/tfuzz.2016.2639565.

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Rezaee, Babak. "Desulfurization process using Takagi–Sugeno–Kang fuzzy modeling." International Journal of Advanced Manufacturing Technology 46, no. 1-4 (2009): 191–97. http://dx.doi.org/10.1007/s00170-009-2031-x.

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Kim, Euntai, Heejin Lee, Chang-Hoon Lee, and Jung-Hwan Kim. "Moving Genetic Algorithm Based Fuzzy Modeling." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 4 (1999): 320–25. http://dx.doi.org/10.20965/jaciii.1999.p0320.

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We propose an approach to Takagi-Sugeno fuzzy modeling via a genetic algorithm consisting of 2 tuning steps - coarse and fine. A moving genetic algorithm (MGA) is proposed and used for fine tuning to obtain robust modeling results. Simulation results demonstrate the algorithm’s validity.
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Wang, Jin, Longze Hu, Fuyang Chen, and Changyun Wen. "Multiple-step fault estimation for interval type-II T-S fuzzy system of hypersonic vehicle with time-varying elevator faults." International Journal of Advanced Robotic Systems 14, no. 2 (2017): 172988141769914. http://dx.doi.org/10.1177/1729881417699149.

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This article proposes a multiple-step fault estimation algorithm for hypersonic flight vehicles that uses an interval type-II Takagi–Sugeno fuzzy model. An interval type-II Takagi–Sugeno fuzzy model is developed to approximate the nonlinear dynamic system and handle the parameter uncertainties of hypersonic firstly. Then, a multiple-step time-varying additive fault estimation algorithm is designed to estimate time-varying additive elevator fault of hypersonic flight vehicles. Finally, the simulation is conducted in both aspects of modeling and fault estimation; the validity and availability of
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Alshammari, Badr, Rim Ben Salah, Omar Kahouli, and Lioua Kolsi. "Design of Fuzzy TS-PDC Controller for Electrical Power System via Rules Reduction Approach." Symmetry 12, no. 12 (2020): 2068. http://dx.doi.org/10.3390/sym12122068.

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In this paper, a new Takagi–Sugeno Fuzzy Logic controller (TS-FLC) is presented and applied for modeling and controlling the nonlinear power systems even in the presence of disturbances. Firstly, a nonlinear mathematical model for the electrical power system is presented with consideration of PSS and AVR controller. Then, a Takagi–Sugeno Fuzzy Logic controller is employed to control power system stability. Nevertheless, the study of the stability of Takagi–Sugeno fuzzy models will be difficult in the case where the number of nonlinearities is important. To cope with this problem, this study pr
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Dissertations / Theses on the topic "Takagi-Sugeno modeling"

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Martinez, Vinícius Machado [UNESP]. "Sistema baseado em regras fuzzy do tipo Takagi-Sugeno aplicado a ecos de radares meteorológicos." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/136276.

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Submitted by Vinicius Machado Martinez null (vinicius@ipmet.unesp.br) on 2016-03-11T20:20:53Z No. of bitstreams: 1 defesa.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (MD5)<br>Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-03-15T17:11:38Z (GMT) No. of bitstreams: 1 martinez_vm_me_soro.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (MD5)<br>Made available in DSpace on 2016-03-15T17:11:38Z (GMT). No. of bitstreams: 1 martinez_vm_me_soro.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (M
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Srinivasarengan, Krishnan. "Estimation d'état, estimation paramétrique et identifiabilité des modèles quasi-LPV." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0059/document.

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Dans cette thèse, deux problèmes liés aux approches basées sur des modèles pour le diagnostic de défauts et l'estimation du niveau de dégradation des équipements dans un bâtiment sont étudiés: la conception d'observateurs adaptatifs pour l'estimation de l'état et des paramètres, et l'analyse de l'identifiabilité des paramètres. La classe des modèles considérés est celle des modèles quasi-linéaires à paramètres variants dans le temps (quasi-LPV) avec paramétrisation affine des matrices d'état. Utilisant l'approche polytopique de Takagi-Sugeno (T-S), deux types d'observateurs sont proposés, un p
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Srinivasarengan, Krishnan. "Estimation d'état, estimation paramétrique et identifiabilité des modèles quasi-LPV." Electronic Thesis or Diss., Université de Lorraine, 2018. http://www.theses.fr/2018LORR0059.

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Dans cette thèse, deux problèmes liés aux approches basées sur des modèles pour le diagnostic de défauts et l'estimation du niveau de dégradation des équipements dans un bâtiment sont étudiés: la conception d'observateurs adaptatifs pour l'estimation de l'état et des paramètres, et l'analyse de l'identifiabilité des paramètres. La classe des modèles considérés est celle des modèles quasi-linéaires à paramètres variants dans le temps (quasi-LPV) avec paramétrisation affine des matrices d'état. Utilisant l'approche polytopique de Takagi-Sugeno (T-S), deux types d'observateurs sont proposés, un p
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Tran, Van Nhu. "Amélioration de l'agrément de conduite via le pilotage du groupe motopropulseur." Phd thesis, Université de Valenciennes et du Hainaut-Cambresis, 2013. http://tel.archives-ouvertes.fr/tel-00871807.

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La transmission à double embrayage a été introduite dans les véhicules afin d'améliorer le confort de conduit, l'économie de conduite et de diminuer le temps de changement de vitesses. La gestion du double embrayage joue un rôle important sur le confort de conduite. L'objectif principal de ce travail concerne alors la synthèse des lois de commande du double embrayage en phase de décollage et lors du changement de vitesses. Le mémoire est structuré de la façon suivante : le premier chapitre propose un état de l'art sur le groupe motopropulseur, la modélisation et la commande du groupe motopropu
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Pucciarelli, Amilcar Jose. "Modelagem de series temporais discretas utilizando modelo nebuloso Takagi-Sugeno." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258790.

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Orientador: Gilmar Barreto<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-04T17:28:20Z (GMT). No. of bitstreams: 1 Pucciarelli_AmilcarJose_M.pdf: 3241769 bytes, checksum: cfad3cee97a35c84df363b3a8578479d (MD5) Previous issue date: 2005<br>Resumo: Este estudo primeiramente investiga fundamentos teóricos para análise, desenvolvimento e implementação de algoritmos para modelagem de dados de sistemas dinâmicos e de séries temporais com a finalidade de predição. As séries temporais utilizadas
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Medeiros, Anderson Vinicius de. "Modelagem de sistemas dinamicos não lineares utilizando sistemas fuzzy, algoritmos geneticos e funções de base ortonormal." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261859.

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Orientadores: Wagner Caradori do Amaral, Ricardo Jose Gabrielli Barreto Campello<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-06T08:36:39Z (GMT). No. of bitstreams: 1 Medeiros_AndersonViniciusde_M.pdf: 896535 bytes, checksum: 48d0d75d38fcbbd0f47f7c49823806f1 (MD5) Previous issue date: 2006<br>Resumo: Esta dissertação apresenta uma metodologia para a geração e otimização de modelos fuzzy Takagi-Sugeno (TS) com Funções de Base Ortonormal (FBO) para sistemas dinâmicos não lineares utilizand
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Gurkan, Evren. "Uncertainty Modelling And Stability Analysis For 2-way Fuzzy Adaptive Systems." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/4/734285/index.pdf.

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A novel fuzzy system named as 2-way fuzzy system is developed by combining the intuitionistic fuzzy set theory with the fuzzy systems theory. The developed system is used in modelling and minimizing uncertainty and inconsistency. Uncertainty is the width of the interval introduced by the independent assignment of membership and nonmembership functions of the intuitionistic fuzzy sets<br>and inconsistency is the violation of the consistency inequality in this assignment. The uncertainty and inconsistency is reduced through a 2 phase training. An evaluation of the degree of reduction of inconsis
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Soualmi, Boussaad. "Coopération Homme Machine pour la conduite automatisée : une approche par partage haptique du contrôle." Thesis, Valenciennes, 2014. http://www.theses.fr/2014VALE0007/document.

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Le travail présenté dans la thèse s’inscrit dans le projet de recherche partenarial ANR-ABV 2009 dont l’objet est la conception d’un système de conduite automatisée à basse vitesse. Il décrit et analyse les principes d’un contrôle partagé d’un véhicule automobile entre un conducteur humain et un copilote électronique (E-copilote). L’objectif est de mettre en place une coopération Homme-Machine efficace entre le conducteur et l’E-copilote. Un des enjeux est notamment de permettre au conducteur d’interagir avec l’E-copilote de façon continue pour pouvoir exécuter les manœuvres qu’il souhaite san
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Book chapters on the topic "Takagi-Sugeno modeling"

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Kluska, Jasek. "MISO Takagi-Sugeno Fuzzy System with Linear Membership Functions." In Analytical Methods in Fuzzy Modeling and Control. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89927-3_2.

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Antão, Rómulo, Alexandre Mota, Rui Escadas Martins, and José Tenreiro Machado. "System Modeling Using Type-2 Takagi-Sugeno Fuzzy Systems." In Nonlinear Physical Science. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4633-9_4.

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Chakchouk, Wael, Abderrahmen Zaafouri, and Anis Sallami. "Modeling, Identification and Control of Irrigation Station with Sprinkling: Takagi-Sugeno Approach." In Complex System Modelling and Control Through Intelligent Soft Computations. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12883-2_17.

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Kluska, Jacek. "Transformation Lemma on Analytical Modeling Via Takagi-Sugeno Fuzzy System and Its Applications." In Artificial Intelligence and Soft Computing – ICAISC 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11785231_25.

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Fiordaliso, Antonio. "About the trade-off between accuracy and interpretability of Takagi-Sugeno models in the context of nonlinear time series forecasting." In Interpretability Issues in Fuzzy Modeling. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-37057-4_17.

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Zhe, Quah En, Arif Ahmed Sekh, Chai Quek, and Dilip K. Prasad. "Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) Based Type-2 Diabetic Modeling." In Intelligence Science III. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74826-5_11.

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Huang, Xuefeng, Sucheng Liu, Wei Fang, Qianjin Zhang, and Xiadong Liu. "Large Signal Stability Analysis Based on Takagi-Sugeno Modeling for State Feedback Control of DC Microgrids." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1351-6_7.

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Chadli, Mohammed, Thierry-Marie Guerra, and Ivan Zelinka. "Takagi-Sugeno Fuzzy Representation to Modelling and State Estimation." In Handbook of Optimization. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30504-7_18.

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Park, Ju H., Tae H. Lee, Yajuan Liu, and Jun Chen. "Design of Dissipative Filter for Delayed Nonlinear Interconnected Systems via Takagi-Sugeno Fuzzy Modelling." In Dynamic Systems with Time Delays: Stability and Control. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9254-2_12.

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Rotondo, Damiano, Vicenç Puig, and Fatiha Nejjari. "Model Reference Gain Scheduling Control of a PEM Fuel Cell Using Takagi-Sugeno Modelling." In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08852-5_53.

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Conference papers on the topic "Takagi-Sugeno modeling"

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Tavassoli, Ali, Hamed Jafarian, and Mohammad Eghtesad. "A Fuzzy Nonlinear Modeling of a McPherson Suspension System." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81249.

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The Takagi-Sugeno fuzzy model (TSfm) is a universal approximation of continuous real functions that are defined in a closed and bounded subset of Rn. This strong property of the TSfm can find several applications in modeling of dynamical systems that are described by differential equations. In this paper, we consider Takagi-Sugeno fuzzy model for a McPherson suspension system. One advantage of TSfm is its wide domain of attraction in compare with the other methods. To apply TSf modeling, one must precisely choose the nonlinear terms of the system governing equations. For each nonlinear term, t
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Fan, Donghong, and Lixia Song. "On Stability of Takagi-Sugeno Fuzzy Systems." In 2009 Second International Symposium on Knowledge Acquisition and Modeling. IEEE, 2009. http://dx.doi.org/10.1109/kam.2009.184.

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Alves, Kaike, Rosangela Ballini, and Eduardo Aguiar. "A New Fuzzy Inference System Applied to Time Series Forecasting." In Congresso Brasileiro de Inteligência Computacional. SBIC, 2023. http://dx.doi.org/10.21528/cbic2023-003.

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Fuzzy systems are a class of machine learning introduced by Zadeh that combine accuracy and interpretability. This class of models consists of two main parts, the antecedent and the consequent. While the antecedent is responsible for modeling the inputs, the consequent concerns modeling the output. The literature reports two main types of fuzzy systems: Mamadani and Takagi-Sugeno. While Mamdani uses fuzzy sets in the consequent part, Takagi-Sugeno uses polynomial functions. Consequently, Mamdani provides better understandable models and Takagi-Sugeno more accurate ones. In this paper, we propo
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Hsiao, Ming-Ying, Chi-Hua Liu, Shun-Hung Tsai, Kun-Lin Tsai, Pei-Shin Chen, and Ta-Tau Chen. "A Takagi-Sugeno fuzzy-model-based modeling method." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584132.

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He, Yaofeng, Shangfeng Du, Lijun Chen, and Meihui Liang. "Identification of greenhouse climate using Takagi-Sugeno fuzzy modeling." In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8242840.

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Ramyar, Saina, Mohammad Gorji Sefidmazgi, Seifemichael Amsalu, Ali Karimoddini, Arda Kurt, and Abdollah Homaifar. "Modeling Driver Behavior at Intersections with Takagi-Sugeno Fuzzy Models." In 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015). IEEE, 2015. http://dx.doi.org/10.1109/itsc.2015.384.

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Petritoli, En rico, Fabio Leccese, and Marco Cagnetti. "Takagi-Sugeno Discrete Fuzzy Modeling: an IoT Controlled ABS for UAV." In 2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT). IEEE, 2019. http://dx.doi.org/10.1109/metroi4.2019.8792915.

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Ren, Qun, Luc Baron, and Marek Balazinski. "Type-2 Takagi-Sugeno-Kang Fuzzy Logic Modeling using Subtractive Clustering." In 2006 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE, 2006. http://dx.doi.org/10.1109/nafips.2006.365871.

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Wang, Yue, Dong Sun, Bin Jiang, and Ning-yun Lu. "Takagi-Sugeno fuzzy inference based cascaded hybrid modeling and fault diagnosis." In 2013 25th Chinese Control and Decision Conference (CCDC). IEEE, 2013. http://dx.doi.org/10.1109/ccdc.2013.6561820.

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Schulte, Horst. "Control-Oriented Modeling of Hydrostatic Transmissions using Takagi-Sugeno Fuzzy Systems." In 2007 IEEE International Fuzzy Systems Conference. IEEE, 2007. http://dx.doi.org/10.1109/fuzzy.2007.4295677.

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Reports on the topic "Takagi-Sugeno modeling"

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Event-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, 2022. http://dx.doi.org/10.4271/2022-01-5056.

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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the
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