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1

Speed control of doubly fed induction motor using backstepping control with interval type-2 fuzzy controller

Herizi Abdelghafour, Rouabhi Riyadh, Zemmit Abderrahim

Diagnostyka

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2023

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Vol. 24, No. 3

art. no. 2023301

EN

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.

2

Decoupling vector control and optimisation of PMSG-based wind energy system using adaptive type-1 and type-2 fuzzy logic control

Mekki Mustapha, Tayeb Allaoui, Belabbas Belkacem, Mouloud Denai

Przegląd Elektrotechniczny

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2020

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R. 96, nr 8

112--116

EN

Variable-speed wind energy conversion systems based on permanent magnet synchronous generators (PMSG) are becoming increasingly popular over the recent years and PMSGs are being adopted by many wind turbine manufacturers especially due to several advantages such as high energy density, low maintenance, self-excitation and direct-drive operation. Vector control is currently the most widely used control strategyin PMSGs to achieve decoupling between the magnetic flux and torguqe via the direct and quadrature components of the current respectively.The major disadvantage of this method is the use of current sensors to ensure accurate decoupling. In this work, a decoupling vector control strategy based on Type-1 and Type-2 fuzzy logic is proposed eliminating the use of current sensors. In addition, a maximum power point tracking (MPPT) technique is proposed to optimise the power extracted from the wind turbine system. Two speed control methodes based on adaptive Type-1 and Type-2 fuzzy logic fractional proportional and integral (PI) controllers. Several simulations are presented to demonstrated the effectiveness of the proposed control schemes for the PMSG-based wind energy conversion system.

PL

Generator synchroniczny z magnesem trwałym PMSG odgrywa kluczową rolę w konwersji energii wiatru (WECS). Sterowanie wektorowe było najczęściej stosowane jako strategia sterowania dla tego generatora w celu zapewnienia oddzielenia prądu stałego od kwadratury. Wadą tej metody jest to, że potrzebuje czujników prądu, aby zapewnić oddzielenie. Artykuł koncentruje się na sterowaniu wektorem oddzielającym opartym na logice rozmytej typu 1 (DFLC1_VC) i logice rozmytej typu 2 (DFLC2_VC). Możemy zapewnić kontrolę systemu, a oddzielenie bez użycia czujników prądu zapewnia kontrolę i odsprzęgnięcie w tym samym czasie. Wyniki symulacji wykazały skuteczność proponowanych strategii kontroli WECS w oparciu o PMSG.

3

Research trends on fuzzy logic controller for mobile robot navigation : a scientometric study

Rani Somiya, Jain Amita, Castillo Oscar

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 1

87--108

EN

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.

4

Nephropathy forecasting in diabetic patients using a GA-based type-2 fuzzy regression model

Shafaei Bajestani N., Vahidian Kamyad A., Nasli Esfahani E., Zare A.

Biocybernetics and Biomedical Engineering

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2017

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Vol. 37, no. 2

281--289

EN

Choosing a proper method to predict and timely prevent the complications of diabetes could be considered a significant step toward optimally controlling the disease. Since in medical research only small sample sizes of data are available and medical data always includes high levels of uncertainty and ambiguity, a type-2 fuzzy regression model seems to be an appropriate procedure for finding the relationship between outcome and explanatory variables in medical decision-making. In this paper, a new type-2 fuzzy regression model based on type-2 fuzzy time series concepts is used to forecast nephropathy in diabetic patients. Results in two examples show model efficiency. The use of such models in diabetes clinics is proposed.

5

Type-2 fuzzy logic controller for a mobile robot

Oryńczak G., Martyna J.

Studia Informatica

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2009

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Vol. 30, nr 2A

121-129

EN

In this paper, we present a new reasoning system based on type-2 fuzzy logic applied to mobile robot controlling. Our system allows for the processing of imprecise and uncertain variables. It has been shown that this approach indicates the imprecision better than type-1 fuzzy logic system, especially where uncertainties are great or are of a linguistic nature. It has been also seen that the prepared type-2 fuzzy inference system allows us to fit our application in navigation in real-time.

PL

W pracy przedstawiono zastosowanie zbiorów rozmytych typu 2 dla budowy sterownika ruchomego robota. Na podstawie opracowanego procesu wnioskowania w systemach przedziałowych wyrażono stopień aktywacji reguły ze sporządzonej uprzednio bazy reguł rozmytych, co umożliwia sterowanie szybkością i kierunkiem ruchu robota.

6

Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and its Optimization with Genetic Algorithms

Hidalgo D., Castillo O., Melin P.

Journal of Automation Mobile Robotics and Intelligent Systems

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2008

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Vol. 2, No. 1

59-73

EN

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.