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Journal articles on the topic 'Takagi Sugeno (TS) fuzzy models'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

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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2

Chiu and Peng. "Design of Takagi-Sugeno Fuzzy Control Scheme for Real World System Control." Sustainability 11, no. 14 (2019): 3855. http://dx.doi.org/10.3390/su11143855.

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In this study, a novelty dual Takagi-Sugeno (TS) fuzzy control scheme (DTSFCS) is proposed for real world system control. We propose using a ball robot (BR) system control problem, where the BR has the ability to move omnidirectionally. The proposed control scheme combines two fuzzy control approaches for a BR. In this fuzzy control approach, the TS fuzzy model was adopted for the fuzzy modeling of the BR. The concept of parallel distributed compensation (PDC) was utilized to develop a fuzzy control scheme from the TS fuzzy models. The linear matrix inequalities (LMIs) can formulate sufficient

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3

Houili, Rabiaa, Mohamed Yacine Hammoudi, Mohamed Benbouzid, and Abdennacer Titaouine. "Observer-Based Controller Using Line Integral Lyapunov Fuzzy Function for TS Fuzzy Systems: Application to Induction Motors." Machines 11, no. 3 (2023): 374. http://dx.doi.org/10.3390/machines11030374.

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This paper deals with the stabilization problem of a nonlinear system described by a Takagi–Sugeno fuzzy (TSF) model with unmeasurable premise variables via a robust controller. Applying the sector nonlinearity techniques, the nonlinear system is represented by a decoupled fuzzy model. Then, we design a robust observer-based controller for the obtained fuzzy system by utilizing the differential mean value approach. The observer and controller gains are obtained by the separation principle, in which the problem is solved in the sum of linear matrix inequalities (LMIs). The paper presents two ma

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4

Youssef, T., M. Chadli, H. R. Karimi, and M. Zelmat. "Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer." Abstract and Applied Analysis 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/670878.

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This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input withkth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The

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Karama, Karama Khamis, and Cenk Ulu. "Internal Model Control Design for Nonlinear Systems Based on Inverse Dynamic Takagi–Sugeno Fuzzy Model." Processes 12, no. 7 (2024): 1334. http://dx.doi.org/10.3390/pr12071334.

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In recent years, applications of inverse model-based control techniques have experienced significant growth in popularity and have been widely used in engineering applications, mainly in nonlinear control system design problems. In this study, a novel fuzzy internal model control (IMC) structure is presented for single-input-single-output (SISO) nonlinear systems. The proposed structure uses the forward and inverse dynamic Takagi–Sugeno (D-TS) fuzzy models of the nonlinear system within the IMC framework for the first time in literature. The proposed fuzzy IMC is obtained in a two-step procedu

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Ellouze, Ameni, Omar Kahouli, Mohamed Ksantini, Ali Rebhi, Nidhal Hnaien, and François Delmotte. "Continuous Stability TS Fuzzy Systems Novel Frame Controlled by a Discrete Approach and Based on SOS Methodology." Mathematics 9, no. 23 (2021): 3129. http://dx.doi.org/10.3390/math9233129.

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Generally, the continuous and discrete TS fuzzy systems’ control is studied independently. Unlike the discrete systems, stability results for the continuous systems suffer from conservatism because it is still quite difficult to apply non-quadratic Lyapunov functions, something which is much easier for the discrete systems. In this paper and in order to obtain new results for the continuous case, we proposed to connect the continuous with the discrete cases and then check the stability of the continuous TS fuzzy systems by means of the discrete design approach. To this end, a novel frame was p

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7

Kamal, Elkhatib, Magdy Koutb, Abdul Azim Sobaih, and Sahar Kaddah. "Maximum Power Control of Hybrid Wind-Diesel-Storage System." Advances in Fuzzy Systems 2008 (2008): 1–9. http://dx.doi.org/10.1155/2008/963710.

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Extraction of maximum wind power of variable speed wind turbines in hybrid wind-diesel-storage system (HWDSS) is considered due to economical purposes. The proposed control algorithm utilizes extended fuzzy-linear matrix equalities (FLMEs) systems design of stabilizing fuzzy controllers for nonlinear systems described by Takagi-Sugeno (TS) fuzzy models. The algorithm maximizes the power coefficient for a fixed pitch. Moreover, it reduces the voltage ripple and stabilizes the system over a wide range of wind speed variations. The control scheme is tested for different profiles of wind speed pat

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8

Akgun, O. Burak, and Elcin Kentel. "Ensemble Precipitation Estimation Using a Fuzzy Rule-Based Model." Engineering Proceedings 5, no. 1 (2021): 48. http://dx.doi.org/10.3390/engproc2021005048.

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In this study, a Takagi-Sugeno (TS) fuzzy rule-based (FRB) model is used for ensembling precipitation time series. The TS FRB model takes precipitation predictions of grid-based regional climate models (RCMs) from the EUR11 domain, available from the CORDEX database, as inputs to generate ensembled precipitation time series for two meteorological stations (MSs) in the Mediterranean region of Turkey. For each MS, RCM data that are available at the closest grid to the corresponding MSs are used. To generate the fuzzy rules of the TS FRB model, the subtractive clustering algorithm (SC) is utilize

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9

Zahra, Taif, Lafifi M. Mourad, and Abbassi Haj Ahmed. "Robust Fuzzy Sliding Mode Observer for Faults Detection in Solar Power Plant Application." Instrumentation Mesure Métrologie 19, no. 4 (2020): 281–87. http://dx.doi.org/10.18280/i2m.190405.

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This article deals with the designing of fuzzy sliding mode observer in order to fault diagnosis in solar power plant. Purpose technique enable to the modulated using Takagi-Sugeno (TS) fuzzy models. Principal of proposed observer is to uses for estimate the state vector of the system; a Linear Matrix Inequalities (LMIs) is performed to ensure stability conditions. Foremother, it is deriving a diagnosis signal-residual. The residual is generated by the comparison of measured and estimated output. Proposed approach performance is tested in solar power plant model through numerical results.

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10

Filasová, Anna, and Dušan Krokavec. "H∞Control of Pairwise Distributable Large-Scale TS Fuzzy Systems." Mathematical Problems in Engineering 2013 (2013): 1–18. http://dx.doi.org/10.1155/2013/874085.

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The paper presents new conditions suitable in design of the stabilizing state controller for a class of continuous-time nonlinear systems, which are representable by pairwise distributable Takagi-Sugeno models. Taking into account the affine properties of the TS model structure and applying the pairwise subsystems fuzzy control scheme relating to the parallel distributed output compensators, the extended bounded real lemma form and the sufficient design conditions for pairwise decentralized control are outlined in terms of linear matrix inequalities. The proposed procedure decouples the Lyapun

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11

Dec, Grzegorz, Grzegorz Drałus, Damian Mazur, and Bogdan Kwiatkowski. "Forecasting Models of Daily Energy Generation by PV Panels Using Fuzzy Logic." Energies 14, no. 6 (2021): 1676. http://dx.doi.org/10.3390/en14061676.

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This paper contains studies of daily energy production forecasting methods for photovoltaic solar panels (PV panel) by using mathematical methods and fuzzy logic models. Mathematical models are based on analytic equations that bind PV panel power with temperature and solar radiation. In models based on fuzzy logic, we use Adaptive-network-based Fuzzy Inference Systems (ANFIS) and the zero-order Takagi-Sugeno model (TS) with specially selected linear and non-linear membership functions. The use of mentioned membership functions causes that the TS system is equivalent to a polynomial and its pro

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12

Ellouze, Ameni, François Delmotte, Jimmy Lauber, Mohamed Chtourou, and Mohamed Ksantini. "Decay rate performance approach for stabilization continuous fuzzy models using their discretized forms." International Journal of Intelligent Computing and Cybernetics 8, no. 4 (2015): 383–400. http://dx.doi.org/10.1108/ijicc-06-2015-0020.

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Purpose – The purpose of this paper is to deal with the stabilization of the continuous Takagi Sugeno (TS) fuzzy models using their discretized forms based on the decay rate performance approach. Design/methodology/approach – This approach is structured as follows: first, a discrete model is obtained from the discretization of the continuous TS fuzzy model. The discretized model is obtained from the Euler approximation method which is used for several orders. Second, based on the decay rate stabilization conditions, the gains of a non-PDC control law ensuring the stabilization of the discrete

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13

et al., Alkaik. "A Takagi-Sugeno model approach for robust fuzzy control design for trajectory tracking of non-linear systems." International Journal of ADVANCED AND APPLIED SCIENCES 9, no. 3 (2022): 159–64. http://dx.doi.org/10.21833/ijaas.2022.03.018.

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This article investigates the robust fuzzy tracking control design for a class of uncertain nonlinear systems using the Takagi–Sugeno (TS) fuzzy models. The main purpose of this study is to design state feedback and observer-based controllers such that the closed-loop system is asymptotically stable. Based on the Lyapunov theory, sufficient conditions are derived such that the closed-loop system is robustly stable. The linear matrix inequality LMI approach is used to obtain the state-feedback and observer gains. The effectiveness of the proposed design approach is provided via numerical simula

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et al., Alsaket. "Robust fuzzy control for non-linear systems with uncertainties: A Takagi- Sugeno model approach." International Journal of ADVANCED AND APPLIED SCIENCES 9, no. 5 (2022): 32–36. http://dx.doi.org/10.21833/ijaas.2022.05.004.

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This article studies the problem of robust control design for a class of uncertain nonlinear systems using the Takagi–Sugeno (TS) fuzzy models. The objective of this study is to design state feedback and an observer-based controller such that the closed-loop system is asymptotically stable. For this purpose, sufficient conditions are derived, and the corresponding controllers are designed by solving a set of linear matrix inequalities (LMIs). The effectiveness of the proposed design approach is provided via numerical simulations for a permanent magnet synchronous motor (PMSM).

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15

Himmelsbach, Matthias, and Andreas Kroll. "On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix." International Journal of Fuzzy Systems 24, no. 2 (2021): 1012–24. http://dx.doi.org/10.1007/s40815-021-01185-9.

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AbstractThis paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models based on the Fisher Information Matrix (FIM). The FIM is used to estimate the covariance matrix of a parameter estimate. It depends on the model parameters as well as the regression variables. Due to the dependency on the model parameters good initial models are required. Since the FIM is a matrix, a scalar measure of the FIM is optimized. Different measures and optimization goals are investigated in three case studies.

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16

Tapia-Herrera, Ricardo, Jesús Alberto Meda-Campaña, Samuel Alcántara-Montes, Tonatiuh Hernández-Cortés, and Lizbeth Salgado-Conrado. "Tuning of a TS Fuzzy Output Regulator Using the Steepest Descent Approach and ANFIS." Mathematical Problems in Engineering 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/873430.

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The exact output regulation problem for Takagi-Sugeno (TS) fuzzy models, designed from linear local subsystems, may have a solution if input matrices are the same for every local linear subsystem. Unfortunately, such a condition is difficult to accomplish in general. Therefore, in this work, an adaptive network-based fuzzy inference system (ANFIS) is integrated into the fuzzy controller in order to obtain the optimal fuzzy membership functions yielding adequate combination of the local regulators such that the output regulation error in steady-state is reduced, avoiding in this way the aforeme

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17

Dhikra, Saoudi. "CONTROLLER DESIGN BASED ON FUZZY OBSERVERS FOR T-S FUZZY BILINEAR MODELS." International Journal of Control Theory and Computer Modeling (IJCTCM) 6, no. 1/2 (2016): 01–16. https://doi.org/10.5121/ijctcm.2016.6201.

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This article is devoted to the design of a fuzzy-observer-based control for a class of nonlinear systems with bilinear terms. The class of systems considered is the Takagi-Sugeno (T-S) fuzzy bilinear model. A new procedure to design the observer-based fuzzy controller for this class of systems is proposed. The aim is to design the fuzzy controller and the fuzzy observer of the augmented system separately in order to guarantee that the error between the state and its estimation converges faster to zero. By using the Lyapunov function, sufficient conditions are derived such that the closed-loop

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18

Krokavec, Dušan, and Anna Filasová. "Stabilizing Fuzzy Output Control for a Class of Nonlinear Systems." Advances in Fuzzy Systems 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/294971.

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The paper presents new conditions suitable in design of a stabilizing output controller for a class of continuous-time nonlinear systems, represented by Takagi-Sugeno models. Taking into account the affine properties of the TS model structure and applying the fuzzy control scheme relating to the parallel distributed output compensators, the sufficient design conditions are outlined in terms of linear matrix inequalities. The proposed procedure decouples the Lyapunov matrix and the system parameter matrices in the LMIs and guarantees global stability of the system. Simulation result illustrates

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19

Blanco, Yann, Wilfrid Perruquetti, and Pierre Borne. "Stability and stabilization of nonlinear systems and Takagi-Sugeno's fuzzy models." Mathematical Problems in Engineering 7, no. 3 (2001): 221–40. http://dx.doi.org/10.1155/s1024123x01001624.

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This paper outlines a methodology to study the stability of Takagi-Sugeno's (TS) fuzzy models. The stability analysis of the TS model is performed using a quadratic Liapunov candidate function. This paper proposes a relaxation of Tanaka's stability condition: unlike related works, the equations to be solved are not Liapunov equations for each rule matrix, but a convex combination of them. The coefficients of this sums depend on the membership functions. This method is applied to the design of continuous controllers for the TS model. Three different control structures are investigated, among wh

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20

Liu, Ling, Bao Guo Tang, and Kai Sun. "The Output Power of the PV Power Plant Modeling Based on ANFIS." Advanced Materials Research 1006-1007 (August 2014): 945–54. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.945.

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To find an effective and reasonable method for calculating precisely the output power of the PV power plant, adaptive neuro-fuzzy inference system (ANFIS) based on Takagi-Sugeno (TS) is proposed. Analysis of the various weather factors that affect the output power of the PV power plant, and select the appropriate input ,MATLAB as a tool ,depend on the different input variable to establish different output power of photovoltaic power plants based on the subtractive clustering the ANFIS model .Results show that all the model has a high accuracy and meet the practical engineering application requ

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21

Assawinchaichote, Wudhichai. "Further results on robust fuzzy dynamic systems with LMI D-stability constraints." International Journal of Applied Mathematics and Computer Science 24, no. 4 (2014): 785–94. http://dx.doi.org/10.2478/amcs-2014-0058.

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Abstract This paper examines the problem of designing a robust H∞ fuzzy controller with D-stability constraints for a class of nonlinear dynamic systems which is described by a Takagi-Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust H∞ fuzzy controller that guarantees (i) the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value, and (ii) the closed-loop pol

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Shams, Zahra, and Aref Shahmansoorian. "Fault estimation based on observer for chaotic Lorenz system with bifurcation problem." Transactions of the Institute of Measurement and Control 42, no. 3 (2019): 576–85. http://dx.doi.org/10.1177/0142331219879267.

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In this paper, the simultaneous estimation of the process and sensor fault of a chaotic Lorenz system in a noisy environment is investigated. The problem of the process fault leads to the occurrence of a bifurcation in the Lorenz system. The purpose of this article is to combine the concept of fault and bifurcation. Fault diagnosis of nonlinear systems becomes more practicable when it is managed over Takagi-Sugeno (TS) approximated fuzzy models. TS fuzzy model unknown input observer can estimate faults and states. In this respect, a TS fuzzy model augmented by a proportional plus integral, for

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JAMWAL, PRASHANT, S. Q. XIE, SHAHID HUSSAIN, and KEAN AW. "MODELING PNEUMATIC MUSCLE ACTUATORS: ARTIFICIAL INTELLIGENCE APPROACH." International Journal of Information Acquisition 07, no. 02 (2010): 151–64. http://dx.doi.org/10.1142/s0219878910002130.

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Robot human interaction requires use of safe, compliant and light weight actuators. Conventional linear motors and pneumatic cylinders are normally used to actuate robots to assist and augment human motions. Lately it has been realized that these actuators are not suitable and safe for applications involving human actor. Their large weight, size and stiffer design raise concerns. Pneumatic muscle actuators (PMA) on the other hand are very light weight, compact and have inherent compliance which make them potential candidate for applications involving robot human interaction. Taking on the adva

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Farah, Nabil, M. H. N. Talib, Z. Ibrahim, J. M. Lazi, and Maaspaliza Azri. "Self-tuning Fuzzy Logic Controller Based on Takagi-Sugeno Applied to Induction Motor Drives." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 4 (2018): 1967. http://dx.doi.org/10.11591/ijpeds.v9.i4.pp1967-1975.

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<span>Fuzzy logic controller has been the main focus for many researchers and industries in motor drives. The popularity of Fuzzy Logic Controller (FLC) is due to its reliability and ability to handle parameters changes during load or disturbance. Fuzzy logic design can be visualized in two categories, mamdani design or Takagi-Sugeno (TS). Mamdani type can facilitate the design process, however it require high computational burden especially with big number of rules and experimental testing. This paper, develop Self-Tuning (ST) mechanism based on Takagi-Sugeno (TS) fuzzy type. The mechan

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Kocian, Jiri, Stepan Ozana, and Jiri Koziorek. "An Approach to Optimization of Takagi-Sugeno Type Fuzzy Regulator Parameters by Genetic Algorithm from Mamdani Regulation Surface." Applied Mechanics and Materials 248 (December 2012): 545–50. http://dx.doi.org/10.4028/www.scientific.net/amm.248.545.

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Many scientific papers deals with the usage of fuzzy rules to implement PID control. Fuzzy models, especially the Takagi-Sugeno-type, have received significant attention from various fields of interest. It is very often very difficult to determine all the parameters of the Takagi-Sugeno-type controller. In this paper we present optimization of Takagi-Sugeno-type fuzzy regulator parameters by genetic algorithm. Implementation of universal fuzzy P/PS/PD function block implemented to the PLC Simatic S7 300/400 is introduced. Mamdani model is used as comparative model. Parameters of Takagi-Sugeno-

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Iqbal Ahammed A.K. and Mohammed Fazle Azeem. "Robust Stabilization And Control Of Takagi-Sugeno Fuzzy Systems With Parameter Uncertainties And Disturbances Via State Feedback And Output Feedback." International Journal of Fuzzy System Applications 9, no. 3 (2020): 63–99. http://dx.doi.org/10.4018/ijfsa.2020070104.

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Most of the systems in the industry contain extreme non-linearity and uncertainties, which are hard to design and control utilizing general nonlinear systems. To conquer this sort of troubles, different plans have been produced in the most recent two decades, among which a popular methodology is Takagi-Sugeno fuzzy control. In this article, we present robust stabilization and control of Takagi-Sugeno (T-S) fuzzy systems with parameter uncertainties and disturbances. Initially, Takagi and Sugeno (TS) fuzzy model is used to represent a nonlinear system. Based on this T-S fuzzy model, fuzzy contr

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Namazov, M., and A. Alili. "Stable and Optimal Controller Design for Takagi-Sugeno Fuzzy Model Based Control Systems via Linear Matrix Inequalities." Information Technologies and Control 14, no. 3 (2016): 31–40. http://dx.doi.org/10.1515/itc-2017-0010.

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AbstractThis paper deals with a systematic design procedure that guarantees the stability and optimal performance of the nonlinear systems described by Takagi-Sugeno fuzzy models. Takagi-Sugeno fuzzy model allows us to represent a nonlinear system by linear models in different state space regions. The overall fuzzy model is obtained by fuzzy blending of these linear models. Then based on this model, linear controllers are designed for each linear model using parallel distributed compensation. Stability and optimal performance conditions for Takagi-Sugeno fuzzy control systems can be represente

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Subiantoro, Aries, F. Yusivar, B. Budiardjo, and M. I. Al-Hamid. "Identification and Control Design of Fuzzy Takagi-Sugeno Model for Pressure Process Rig." Advanced Materials Research 605-607 (December 2012): 1810–18. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1810.

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The design of an intelligent controller based on fuzzy TS model for a pressure process rig is presented. The proposed controller consists of a fuzzy TS model, a feedback fuzzy TS model, and a low pass filter combined in an internal model control structure. The identification of the fuzzy TS model uses fuzzy clustering technique to mimic the nonlinearity characteristic of the process. Instead of least-squares algorithm, the instrumental variable method is used to estimate the consequent parameters of the fuzzy TS model in order to avoid inconsistency problem. The identified model is validated w

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Bahou, Omar, Mohammed Roudani, and Karim El Moutaouakil. "G-TS-HRNN: Gaussian Takagi–Sugeno Hopfield Recurrent Neural Network." Information 16, no. 2 (2025): 141. https://doi.org/10.3390/info16020141.

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The Hopfield Recurrent Neural Network (HRNN) is a single-point descent metaheuristic that uses a single potential solution to explore the search space of optimization problems, whose constraints and objective function are aggregated into a typical energy function. The initial point is usually randomly initialized, then moved by applying operators, characterizing the discrete dynamics of the HRNN, which modify its position or direction. Like all single-point metaheuristics, HRNN has certain drawbacks, such as being more likely to get stuck in local optima or miss global optima due to the use of

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Hsiao, Feng-Hsiag, and Wei-Ling Chiang. "Application of Fuzzy H∞ Control via T–S Fuzzy Models for Nonlinear Time-Delay Systems." International Journal on Artificial Intelligence Tools 12, no. 02 (2003): 117–37. http://dx.doi.org/10.1142/s0218213003001174.

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This paper deals with the problem of stability analysis and stabilization via Takagi-Sugeno (T-S) fuzzy models for nonlinear time-delay systems. First, Takagi-Sugeno (T-S) fuzzy models and some stability results are recalled. To design fuzzy controllers, nonlinear time-delay systems are represented by Takagi-Sugeno fuzzy models. The concept of parallel-distributed compensation (PDC) is employed to determine structures of fuzzy controllers from the T-S fuzzy models. LMI-based design problems are defined and employed to find feedback gains of fuzzy controller and common positive definite matrice

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Chen, Shinn-Horng, Wen-Hsien Ho, and Jyh-Horng Chou. "Robust Local Regularity and Controllability of Uncertain TS Fuzzy Descriptor Systems." Journal of Applied Mathematics 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/825416.

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The robust local regularity and controllability problem for the Takagi-Sugeno (TS) fuzzy descriptor systems is studied in this paper. Under the assumptions that the nominal TS fuzzy descriptor systems are locally regular and controllable, a sufficient criterion is proposed to preserve the assumed properties when the structured parameter uncertainties are added into the nominal TS fuzzy descriptor systems. The proposed sufficient criterion can provide the explicit relationship of the bounds on parameter uncertainties for preserving the assumed properties. An example is given to illustrate the a

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Enemegio, Rodolfo, Francisco Jurado, and Jonathan Villanueva-Tavira. "Experimental Evaluation of a Takagi–Sugeno Fuzzy Controller for an EV3 Ballbot System." Applied Sciences 14, no. 10 (2024): 4103. http://dx.doi.org/10.3390/app14104103.

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In this paper, experimental results about the performance of a Takagi–Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration of the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. In this work, following the Takagi–Sugeno (TS) fuzzy control design methodology, the Parallel Distributed Compensation (PDC) approach is used in the design of the TSFC. The EV3BRS’s TS Fuzzy Model (TSFM) design comes from linearization of the nonlinear mod

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Chaubey, Shivam, and Vicenç Puig. "Autonomous Vehicle State Estimation and Mapping Using Takagi–Sugeno Modeling Approach." Sensors 22, no. 9 (2022): 3399. http://dx.doi.org/10.3390/s22093399.

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This paper proposes an optimal approach for state estimation based on the Takagi–Sugeno (TS) Kalman filter using measurement sensors and rough pose obtained from LIDAR scan end-points matching. To obtain stable and optimal TS Kalman gain for estimator design, a linear matrix inequality (LMI) is optimized which is constructed from Lyapunov stability criteria and dual linear quadratic regulator (LQR). The technique utilizes a Takagi–Sugeno (TS) representation of the system, which allows modeling the complex nonlinear dynamics in such a way that linearization is not required for the estimator or

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Niu, Yiran, Xiaofeng Xu, and Ming Liu. "Fixed Time Synchronization of Stochastic Takagi–Sugeno Fuzzy Recurrent Neural Networks with Distributed Delay under Feedback and Adaptive Controls." Axioms 13, no. 6 (2024): 391. http://dx.doi.org/10.3390/axioms13060391.

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In this paper, the stochastic Takagi–Sugeno fuzzy recurrent neural networks (STSFRNNS) with distributed delay is established based on the Takagi–Sugeno (TS) model and the fixed time synchronization problem is investigated. In order to synchronize the networks, we design two kinds of controllers: a feedback controller and an adaptive controller. Then, we obtain the synchronization criteria in a fixed time by combining the Lyapunov method and the related inequality theory of the stochastic differential equation and calculate the stabilization time for the STSFRNNS. In addition, to verify the aut

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Jovanovic, Radisa, and Vladimir Zaric. "Identification and control of a heat flow system based on the Takagi-Sugeno fuzzy model using the grey wolf optimization algorithm." Thermal Science, no. 00 (2021): 324. http://dx.doi.org/10.2298/tsci210825324j.

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Even though, it is mostly used by process control engineers, the temperature control remains an important task for researchers. This paper addressed two separate issues concerning model optimization and control. Firstly, the linear models for the three different operating points of the heat flow system were found. From these identified models a Takagi-Sugeno model is obtained using fixed membership functions in the premises of the rules. According to the chosen objective function, parameters in the premise part of Takagi-Sugeno fuzzy model were optimized using the grey wolf algorithm. Furtherm

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Jafari, Sadiqa, Zeinab Shahbazi, and Yung-Cheol Byun. "Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections." Mathematics 10, no. 16 (2022): 2832. http://dx.doi.org/10.3390/math10162832.

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Traffic congestion is a significant issue in many countries today. The suggested method is a novel control method based on multiple intersections considering the kind of traffic light and the duration of the green phase to determine the optimal balance at intersections by using fuzzy logic control, for which the balance should be adaptable to the unchanging behavior of time. It should reduce traffic volume in transport, average waits for each vehicle, and collisions between cars by controlling this balance in response to the typical behavior of time and randomness in traffic conditions. The pr

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Precup, Radu-Emil, Marius L. Tomescu, and Stefan Preitl. "Lorenz System Stabilization Using Fuzzy Controllers." International Journal of Computers Communications & Control 2, no. 3 (2007): 279. http://dx.doi.org/10.15837/ijccc.2007.3.2360.

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The paper suggests a Takagi Sugeno (TS) fuzzy logic controller (FLC) designed to stabilize the Lorentz chaotic systems. The stability analysis of the fuzzy control system is performed using Barbashin-Krasovskii theorem. This paper proves that if the derivative of Lyapunov function is negative semi-definite for each fuzzy rule then the controlled Lorentz system is asymptotically stable in the sense of Lyapunov. The stability theorem suggested here offers sufficient conditions for the stability of the Lorenz system controlled by TS FLCs. An illustrative example describes the application of the n

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Nelles, Oliver. "Structure Optimization of Takagi-Sugeno Fuzzy Models." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 06, no. 02 (1998): 161–70. http://dx.doi.org/10.1142/s0218488598000148.

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A new approach for nonlinear system identification based on Takagi-Sugeno fuzzy models is presented. The premise structure and membership functions are optimized by the LOLIMOT (local linear model tree) algorithm, see [1]. This method is extended by a subset selection technique which automatically determines the structure of the local linear models in the rule consequents. This allows to select the significant input variables for static models and additionally the determination of the dynamic orders and dead times for dynamic models. The utilized subset selection technique is the orthogonal le

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Marie Guerra, Thierry, and Laurent Vermeiren. "Control laws for Takagi–Sugeno fuzzy models." Fuzzy Sets and Systems 120, no. 1 (2001): 95–108. http://dx.doi.org/10.1016/s0165-0114(99)00058-5.

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Johansen, T. A., and R. Babuska. "Multiobjective identification of Takagi-Sugeno fuzzy models." IEEE Transactions on Fuzzy Systems 11, no. 6 (2003): 847–60. http://dx.doi.org/10.1109/tfuzz.2003.819824.

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Liutkevičius, R. "Fuzzy Hammerstein Model of Nonlinear Plant." Nonlinear Analysis: Modelling and Control 13, no. 2 (2008): 201–12. http://dx.doi.org/10.15388/na.2008.13.2.14580.

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This paper presents the synthesis and analysis of the enhanced predictive fuzzy Hammerstein model of the water tank system. Fuzzy Hammerstein model was compared with three other fuzzy models: the first was synthesized using Mamdani type rule base, the second – Takagi-Sugeno type rule base and the third – composed of Mamdani and Takagi-Sugeno rule bases. The synthesized model is invertible so it can be used in the model based control. The fuzzy Hammerstein model was synthesized to eliminate disadvantages of the other fuzzy models. The advantage of the fuzzy Hammerstein model was experimentally

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Jonnalagadda, Vimala Kumari, Vinodh Kumar Elumalai, Harvir Singh, and Amit Prasad. "Nonlinear control design using Takagi-Sugeno fuzzy applied to under-actuated visual servo system." Transactions of the Institute of Measurement and Control 42, no. 15 (2020): 2969–83. http://dx.doi.org/10.1177/0142331220936584.

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This paper presents the Takagi-Sugeno (TS) fuzzy control design for nonlinear stabilization and tracking control of a ball on plate system. To deal with the plant nonlinearity and the fuzzy convergence issue, we formulate the parallel distributed compensator (PDC) TS fuzzy model to characterize the global behaviour of the nonlinear system and synthesize a feasible control framework using a velocity compensation scheme. The nonlinear dynamics of the ball on plate system is obtained using the Euler-Lagrangian energy based approach. To identify the moving objects in the video stream, a background

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Precup, Radu-Emil, Stefan Preitl, Claudia-Adina Bojan-Dragos, et al. "AUTOMOTIVE APPLICATIONS OF EVOLVING TAKAGI-SUGENO-KANG FUZZY MODELS." Facta Universitatis, Series: Mechanical Engineering 15, no. 2 (2017): 231. http://dx.doi.org/10.22190/fume170505011p.

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This paper presents theoretical and application results concerning the development of evolving Takagi-Sugeno-Kang fuzzy models for two dynamic systems, which will be viewed as controlled processes, in the field of automotive applications. The two dynamic systems models are nonlinear dynamics of the longitudinal slip in the Anti-lock Braking Systems (ABS) and the vehicle speed in vehicles with the Continuously Variable Transmission (CVT) systems. The evolving Takagi-Sugeno-Kang fuzzy models are obtained as discrete-time fuzzy models by incremental online identification algorithms. The fuzzy mod

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Zuo, Hua, Guangquan Zhang, Witold Pedrycz, Vahid Behbood, and Jie Lu. "Fuzzy Regression Transfer Learning in Takagi–Sugeno Fuzzy Models." IEEE Transactions on Fuzzy Systems 25, no. 6 (2017): 1795–807. http://dx.doi.org/10.1109/tfuzz.2016.2633376.

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Kaewpraek, Nikorn, and Wudhichai Assawinchaichote. "Control of PMSG Wind Energy Conversion System with TS Fuzzy State-Feedback Controller." Applied Mechanics and Materials 446-447 (November 2013): 728–32. http://dx.doi.org/10.4028/www.scientific.net/amm.446-447.728.

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This paper presents a Takagi-Sugeno (TS) fuzzy state-feedback controller based on a linear matrix inequality (LMI) approach for the permanent magnet synchronous generator of wind energy conversion system (PMSG-WECS). A dc/dc converter is considered to regulate the maximum power output of the system. To show its effectiveness, the dynamic model is replaced by the TS fuzzy model, which the proposed controller can be applied to the PMSG-WECS, while the controller gains can be obtained by solving set of a LMI approach. The proposed controller guarantees the stability of the system. Therefore, the

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Oke, Paul, and Sing Kiong Nguang. "Robust H∞ Takagi–Sugeno fuzzy output-feedback control for differential speed steering vehicles." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 12 (2020): 2822–35. http://dx.doi.org/10.1177/0954407020918705.

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This paper studied the modelling and control of four-wheel independently driven electric vehicles using differential speed steering. The Takagi–Sugeno fuzzy modelling approach represents the nonlinearities of the four-wheel independently driven electric vehicle state variables in several system models. The proposed controller design is a robust Takagi–Sugeno fuzzy output-feedback control based on a fuzzy Lyapunov function approach. More precisely, the Lyapunov function is chosen to be dependent on the membership functions. Sufficient conditions for the existence of the robust Takagi–Sugeno fuz

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Latrach, Chedia, Mourad Kchaou, Abdelhamid Rabhi, and Ahmed El Hajjaji. "Decentralized networked control system design using Takagi-Sugeno (TS) fuzzy approach." International Journal of Automation and Computing 12, no. 2 (2015): 125–33. http://dx.doi.org/10.1007/s11633-015-0879-9.

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Kukolj, Dragan. "Design of adaptive Takagi–Sugeno–Kang fuzzy models." Applied Soft Computing 2, no. 2 (2002): 89–103. http://dx.doi.org/10.1016/s1568-4946(02)00032-7.

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Angelov, Plamen, José Victor, António Dourado, and Dimitar Filev. "On-Line Evolution of Takagi-Sugeno Fuzzy Models." IFAC Proceedings Volumes 37, no. 16 (2004): 67–72. http://dx.doi.org/10.1016/s1474-6670(17)30852-2.

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Tencer, L., M. Reznakova, and M. Cheriet. "TITS-FM: Transductive incremental Takagi-Sugeno fuzzy models." Applied Soft Computing 26 (January 2015): 531–44. http://dx.doi.org/10.1016/j.asoc.2014.09.024.

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