Wszystkie pola: fuzzy logic type 2 - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Fuzzy synergetic control for dynamic car-like mobile robot
Autorzy:: Bouhamatou, Zoulikha
Abedssemed, Foudil
Powiązania:: https://bibliotekanauki.pl/articles/2106222.pdf
Data publikacji:: 2022
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:: CLMR
synergetic control
lyapunov stability
GWO
fuzzy logic type 2
Opis:: This paper aims to present the dynamic control of a Car-like Mobile Robot (CLMR) using Synergetic Control (SC). The SC control is used to make the linear velocity and steering velocity converge to references. Lyapunov synthesis is adopted to assure controlled system stability. To find the optimised parameters of the SC, the grey wolf optimiser (GWO) algorithm is used. These parameters depend on the best-selected fitness function. Four fitness functions are selected for this purpose, which is based on the integral of the error square (ISE), the integral of the square of the time-weighted error (ITSE), the integral of the error absolute (IAE) and the integral of the absolute of the time-weighted error (TIAE) criterion. To go further in the investigation, fuzzy logic type 2 is used to get at each iteration the appropri-ate controller parameters that give the best performances and robustness. Simulations results are conducted to show the feasibility and efficiency of the proposed control methods.
Źródło:: Acta Mechanica et Automatica; 2022, 16, 1; 48--57
1898-4088
2300-5319
Pojawia się w:: Acta Mechanica et Automatica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: A novel approach to type-reduction and design of interval type-2 fuzzy logic systems
Autorzy:: Starczewski, Janusz T.
Przybyszewski, Krzysztof
Byrski, Aleksander
Szmidt, Eulalia
Napoli, Christian
Powiązania:: https://bibliotekanauki.pl/articles/2147137.pdf
Data publikacji:: 2022
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: smooth type-reduction
interval type-2 fuzzy logic systems
Opis:: Fuzzy logic systems, unlike black-box models, are known as transparent artificial intelligence systems that have explainable rules of reasoning. Type 2 fuzzy systems extend the field of application to tasks that require the introduction of uncertainty in the rules, e.g. for handling corrupted data. Most practical implementations use interval type-2 sets and process interval membership grades. The key role in the design of type-2 interval fuzzy logic systems is played by the type-2 inference defuzzification method. In type-2 systems this generally takes place in two steps: type-reduction first, then standard defuzzification. The only precise type-reduction method is the iterative method known as Karnik-Mendel (KM) algorithm with its enhancement modifications. The known non-iterative methods deliver only an approximation of the boundaries of a type-reduced set and, in special cases, they diminish the profits that result from the use of type-2 fuzzy logic systems. In this paper, we propose a novel type-reduction method based on a smooth approximation of maximum/minimum, and we call this method a smooth type-reduction. Replacing the iterative KM algorithm by the smooth type-reduction, we obtain a structure of an adaptive interval type-2 fuzzy logic which is non-iterative and as close to an approximation of the KM algorithm as we like.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 197--206
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Users-centric adaptive learning system based on interval type-2 fuzzy logic for massively crowded e-learning platforms
Autorzy:: Almohammadi, K.
Hagras, H.
Alghazzawi, D.
Aldabbagh, G.
Powiązania:: https://bibliotekanauki.pl/articles/91622.pdf
Data publikacji:: 2016
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: Type-2 Fuzzy Logic systems
e-learning
intelligent learning environments
Opis:: Technological advancements within the educational sector and online learning promoted portable data-based adaptive techniques to influence the developments within transformative learning and enhancing the learning experience. However, many common adaptive educational systems tend to focus on adopting learning content that revolves around pre-black box learner modelling and teaching models that depend on the ideas of a few experts. Such views might be characterized by various sources of uncertainty about the learner response evaluation with adaptive educational system, linked to learner reception of instruction. High linguistic uncertainty levels in e-learning settings result in different user interpretations and responses to the same techniques, words, or terms according to their plans, cognition, pre-knowledge, and motivation levels. Hence, adaptive teaching models must be targeted to individual learners’ needs. Thus, developing a teaching model based on the knowledge of how learners interact with the learning environment in readable and interpretable white box models is critical in the guidance of the adaptation approach for learners’ needs as well as understanding the way learning is achieved. This paper presents a novel interval type-2 fuzzy logic-based system which is capable of identifying learners’ preferred learning strategies and knowledge delivery needs that revolves around characteristics of learners and the existing knowledge level in generating an adaptive learning environment. We have conducted a large scale evaluation of the proposed system via real-word experiments on 1458 students within a massively crowded e-learning platform. Such evaluations have shown the proposed interval type-2 fuzzy logic system’s capability of handling the encountered uncertainties which enabled to achieve superior performance with regard to better completion and success rates as well as enhanced learning compared to the non-adaptive systems, adaptive system versions led by the teacher, and type-1-based fuzzy based counterparts.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 2; 81-101
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Three-dimensional fuzzy control of ultrasonic cleaning
Autorzy:: Morkun, Volodymyr
Kravchenko, Olha
Powiązania:: https://bibliotekanauki.pl/articles/2115809.pdf
Data publikacji:: 2021
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:: ultrasonic cleaning
3D fuzzy interval type 2 logic
modeling
spatially distributed systems
Opis:: Consideration of ultrasonic cleaning as a process with distributed parameters enables reduction of power consumption. This approach is based on establishment of control over the process depending on fixed values of ultrasonic responses in set points. The initial intensity of radiators is determined using a three-dimensional (3D) interval type-2 fuzzy logic controller essentially created for processes with distributed parameters, as well as complex expert evaluation of the input data. The interval membership functions for the input and output data consider the space heterogeneity of ultrasonic cleaning. A rule base is formed, which is 2D and not dependent upon the number of input and output parameters. A model illustrating ultrasonic cleaning with a 3D interval type-2 fuzzy logic controller is designed. Comparative analysis of the output parameters of the proposed model and the traditional method indicates an increase in the energy efficiency by 41.17% due to application of only those ultrasonic radiators that are located next to the contamination.
Źródło:: Acta Mechanica et Automatica; 2021, 15, 3; 169--176
1898-4088
2300-5319
Pojawia się w:: Acta Mechanica et Automatica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and its Optimization with Genetic Algorithms
Autorzy:: Hidalgo, D.
Castillo, O.
Melin, P.
Powiązania:: https://bibliotekanauki.pl/articles/384559.pdf
Data publikacji:: 2008
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: modular neural networks
type-2 fuzzy logic
pattern recognition
genetic algorithms
Opis:: We describe in this paper a comparative study between Fuzzy Inference Systems as methods of integration in modular neural networks for multimodal biometry. These methods of integration are based on techniques of type-1 fuzzy logic and type-2 fuzzy logic. Also, the fuzzy systems are optimized with simple genetic algorithms. First, we considered the use of type-1 fuzzy logic and later the approach with type-2 fuzzy logic. The fuzzy systems were developed using genetic algorithms to handle fuzzy inference systems with different membership functions, like the triangular, trapezoidal and Gaussian; since these algorithms generate the fuzzy systems automatically. Then the response integration of the modular neural network was tested with the optimized fuzzy integration systems. The comparative study of type-1 and type-2 fuzzy inference systems was made to observe the behavior of the two different integration methods for modular neural networks for multimodal biometry.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 59-73
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: An analytical insight to investigate the research patterns in the realm of Type-2 fuzzy logic
Autorzy:: Vij, S.
Jain, A.
Tayal, D.
Castillo, O.
Powiązania:: https://bibliotekanauki.pl/articles/951726.pdf
Data publikacji:: 2018
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: scientometric analysis
Type 2 fuzzy logic
Type 2 fuzzy systems
Type 2 fuzzy control
Type 2 fuzzy set
analiza scjentometryczna
logika rozmyta typu 2
systemy rozmyte typu 2
Opis:: Fuzzy logic has always been one of the key research areas in the field of computer science as it helps in dealing with the real world vagueness and uncertainty. In recent years, a variant of it, Type-2 Fuzzy Logic has gained enormous popularity for research purposes. In this paper, an analytical insight is provided into the research patterns of Type-2 Fuzzy logic. Web of Science has been used as the data source which consists of Science Citation Index- Expanded (SCI-E), SSCI, A&HCI and ESCI indexed research papers. 600 research papers were extracted from it in the field of Type-2 fuzzy logic from the year 2000 to 2016, which are analyzed both manually and in an automated manner. The performed study is Scientometric in nature and helps in answering research questions like control terms and top authors in this field, the growth pattern in research publications, top funding agencies and countries etc. The major goal of this study is to analyze the research work in type-2 fuzzy logic so as to track the growth of this discipline through the years and envision future trends in this area.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 2; 3-32
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Research trends on fuzzy logic controller for mobile robot navigation : a scientometric study
Autorzy:: Rani, Somiya
Jain, Amita
Castillo, Oscar
Powiązania:: https://bibliotekanauki.pl/articles/384308.pdf
Data publikacji:: 2020
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: fuzzy logic controller
autonomous mobile robot navigation
type-2 fuzzy logic
optimized fuzzy controller
Opis:: The present study shows the scientometric analysis of the publications on the fuzzy logic controller in autonomous mobile robot navigation during the period 2000 to 2018. The data is collected using Web of Science core collection database and analyzed at various levels such as Web of Science categories, publication years, document types, funding agencies, authors, research areas, countries or region, control terms, and organization to evaluate the research patterns. An extensive study is done to find the research trends in this area.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 87-108
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: On the elimination of nonlinear phenomena in DC/DC converters using type-2 fuzzy logic controller
Autorzy:: Gozim, D.
Guesmi, K.
Mahi, D.
Powiązania:: https://bibliotekanauki.pl/articles/329252.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:: power converter
type-2 fuzzy logic controller
bifurcation
chaos
urządzenie przekształtnikowe
logika rozmyta
bifurkacje
Opis:: DC/DC converters are wealthy of nonlinear phenomena that appear when the converter parameters are subject to perturbation or variation. The converter may exhibit bifurcation from behavior to another, quasi periodic and chaotic responses. In such cases, it is difficult and even impossible to analyze, to predict and to control the converter behavior. This paper gives a description of a DC/DC converter and shows their desirable and undesirable behaviors; then a solution, based on type-2 fuzzy logic controller, is proposed to eliminate the undesirable behaviors and to enhance the converter dynamics.
Źródło:: Diagnostyka; 2018, 19, 3; 73-80
1641-6414
2449-5220
Pojawia się w:: Diagnostyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Type-2 fuzzy logic systems in applications: managing data in selective catalytic reduction for air pollution prevention
Autorzy:: Niewiadomski, Adam
Kacprowicz, Marcin
Powiązania:: https://bibliotekanauki.pl/articles/2031133.pdf
Data publikacji:: 2021
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: Selective Catalytic Reduction
SCR
fuzzy management of DeNOx filter
fuzzy logic systems
”engineering” fuzzy implications
learning fuzzy rules
Opis:: The article presents our research on applications of fuzzy logic to reduce air pollution by DeNOx filters. The research aim is to manage data on Selective Catalytic Reduction (SCR) process responsible for reducing the emission of nitrogen oxide (NO) and nitrogen dioxide (NO2). Dedicated traditional Fuzzy Logic Systems (FLS) and Type-2 Fuzzy Logic Systems (T2FLS) are proposed with the use of new methods for learning fuzzy rules and with new types of fuzzy implications (the so-called ”engineering implications”). The obtained results are consistent with the results provided by experts. The main advantage of this paper is that type-2 fuzzy logic systems with ”engineering implications” and new methods of learning fuzzy rules give results closer to expert expectations than those based on traditional fuzzy logic systems. According to the literature review, no T2FLS were applied to manage DeNOx filter prior to the research presented here.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 2; 85-97
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: An Architecture for Making Judgments Using Computing With Words
Autorzy:: Mendel, J. M.
Powiązania:: https://bibliotekanauki.pl/articles/908008.pdf
Data publikacji:: 2002
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: informatyka
computing with words
footprint of uncertainty
perceptual computer
type-2 fuzzy logic system
judgments
Opis:: Our thesis is that computing with words needs to account for the uncertainties associated with the meanings of words, and that these uncertainties require using type-2 fuzzy sets. Doing this leads to a proposed architecture for making judgments by means of computing with words, i.e., to a perceptual computer - the Per-C. The Per-C includes an encoder, a type-2 rule-based fuzzy logic system, and a decoder. It lets all human-computer interactions be performed using words. In this paper, a quantitative language is established for the Per-C, and many open issues about the perceptual computer are described.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 325-335
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Intelligent Control for a Perturbed Autonomous Wheeled Mobile Robot Using Type-2 Fuzzy Logic and Genetic Algorithms
Autorzy:: Martínez, R.
Castillo, O.
Aguilar, L. T.
Powiązania:: https://bibliotekanauki.pl/articles/384492.pdf
Data publikacji:: 2008
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: mobile robot
path planning
fuzzy logic
genetic algorithms
autonomous mobile robot navigation
Opis:: We describe a tracking controller for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on Type-2 Fuzzy Logic Theory and Genetic Algorithms. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 12-22
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: A Big-Bang Big-Crunch optimized general type-2 fuzzy logic approach for Multi-Criteria Group Decision Making
Autorzy:: Naim, S.
Hagras, H.
Powiązania:: https://bibliotekanauki.pl/articles/91606.pdf
Data publikacji:: 2013
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: General Type-2 Fuzzy Logic
Multi-Criteria Group Decision Making
MCGDM
Big Bang-Big Crunch
BB-BC
intelligent apartment
iSpace
Opis:: Multi-Criteria Group Decision Making (MCGDM) aims to find a unique agreement from a number of decision makers/users by evaluating the uncertainty in judgments. In this paper, we present a General Type-2 Fuzzy Logic based approach for MCGDM (GFLMCGDM). The proposed system aims to handle the high levels of uncertainties which exist due to the varying Decision Makers’ (DMs) judgments and the vagueness of the appraisal. In order to find the optimal parameters of the general type-2 fuzzy sets, we employed the Big Bang-Big Crunch (BB-BC) optimization. The aggregation operation in the proposed method aggregates the various DMs opinions which allow handling the disagreements of DMs’ opinions into a unique approval. We present results from an application for the selection of reading lighting level in an intelligent environment. We carried out various experiments in the intelligent apartment (iSpace) located at the University of Essex. We found that the proposed GFL-MCGDM effectively handle the uncertainties between the various decision makers which resulted in producing outputs which better agreed with the users’ decision compared to type 1 and interval type 2 fuzzy based systems.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2013, 3, 2; 117-132
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Triangular fuzzy-rough set based fuzzification of fuzzy rule-based systems
Autorzy:: Starczewski, Janusz T.
Goetzen, Piotr
Napoli, Christian
Powiązania:: https://bibliotekanauki.pl/articles/1837416.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: general type-2 fuzzy logic systems
fuzzy-rough fuzzification
regular type-2 t-norms
cropped triangular secondary membership functions
Opis:: In real-world approximation problems, precise input data are economically expensive. Therefore, fuzzy methods devoted to uncertain data are in the focus of current research. Consequently, a method based on fuzzy-rough sets for fuzzification of inputs in a rulebased fuzzy system is discussed in this paper. A triangular membership function is applied to describe the nature of imprecision in data. Firstly, triangular fuzzy partitions are introduced to approximate common antecedent fuzzy rule sets. As a consequence of the proposed method, we obtain a structure of a general (non-interval) type-2 fuzzy logic system in which secondary membership functions are cropped triangular. Then, the possibility of applying so-called regular triangular norms is discussed. Finally, an experimental system constructed on precise data, which is then transformed and verified for uncertain data, is provided to demonstrate its basic properties.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 4; 271-285
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: A robust fault diagnosis and forecasting approach based on Kalman filter and interval type-2 fuzzy logic for efficiency improvement of centrifugal gas compressor system
Autorzy:: Nail, Bachir
Kouzou, Abdellah
Hafaifa, Ahmed
Hadroug, Nadji
Puig, Vicenç
Powiązania:: https://bibliotekanauki.pl/articles/329190.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:: fault detection
diagnosis
centrifugal gas compressor
Kalman filter
interval type-2 fuzzy logic
experimental data
ARIMA
detekcja uszkodzeń
diagnostyka
filtr Kalmana
Opis:: The paper proposes a robust faults detection and forecasting approach for a centrifugal gas compressor system, the mechanism of this approach used the Kalman filter to estimate and filtering the unmeasured states of the studied system based on signals data of the inputs and the outputs that have been collected experimentally on site. The intelligent faults detection expert system is designed based on the interval type-2 fuzzy logic. The present work is achieved by an important task which is the prediction of the remaining time of the system under study to reach the danger and/or the failure stage based on the Auto-regressive Integrated Moving Average (ARIMA) model, where the objective within the industrial application is to set the maintenance schedules in precisely time. The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.
Źródło:: Diagnostyka; 2019, 20, 2; 57-75
1641-6414
2449-5220
Pojawia się w:: Diagnostyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Speed control of doubly fed induction motor using backstepping control with interval type-2 fuzzy controller
Autorzy:: Herizi, Abdelghafour
Rouabhi, Riyadh
Zemmit, Abderrahim
Powiązania:: https://bibliotekanauki.pl/articles/2232527.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:: double fed induction motor
type-2 fuzzy logic
backstepping control
hybrid control
robust
silnik indukcyjny
logika rozmyta typu 2
kontrola wsteczna
sterowanie hybrydowe
Opis:: The control of the doubly-fed induction motor is a complex operation because of this motor characterised by a non-linear multivariable dynamics, having settings that change over time and a significant link between the mechanical component and magnetic behavior (flux) (speed and couple). This article then proposes a new strategy of a robust control of this motor, which is decoupled due to the stator flux’s direction. The proposed control is integrated with the backstepping control which based on Lyapunov theory; this approach consists in constructively designing a control law of nonlinear systems by considering some state variables as being virtual commands, and the important branch of artificial intelligence type-2 fuzzy logic. The hybrid control backstepping-fuzzy logic consists in replacing the regulators applied to the backstepping control by regulators based on type-2 fuzzy logic. This control will be evaluated by numerous simulations where there is a parametric and non-parametric variation.
Źródło:: Diagnostyka; 2023, 24, 3; art. no. 2023301
1641-6414
2449-5220
Pojawia się w:: Diagnostyka
Dostawca treści:: Biblioteka Nauki

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