Fuzzy logic control strategy of wind generator based on the dual-stator induction generator

Chekkal, Samira; Lahaçani, Narimen Aouzellag; Aouzellag, Djamal; Ghedamsi, Kaci

doi:10.1016/j.ijepes.2014.02.005

Cited by 45 publications

(31 citation statements)

References 12 publications

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“…In the fuzzy self-tuning PID control system [4,5], the deviation and the first derivative of the deviation of the closed-loop system are the inputs of fuzzy controller, p K , i K and d K are the outputs of fuzzy controller. When the inputs change, the output parameters of fuzzy controller would adjust automatically according to the fuzzy rules which based on the control theory and experience.…”

Section: Fuzzy Control For Toroidal Motormentioning

confidence: 99%

Fuzzy Control for Dual-stator Toroidal Motor with Hybrid Excitation

Liu¹,

Wang²

2016

Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

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Abstract. Dual-stator toroidal motor with hybrid excitation is a new-style motor, it integrates power and drive function. The mathematic model of the motor system was derived based on the operating principle of the motor. In order to improve the response characteristic of toroidal motor, a fuzzy self-tuning PID control system was presented and a fuzzy controller was designed based on fuzzy control rules. The response of fuzzy control system with disturbance was simulated. The comparison results justify the better anti-interference ability of the toroidal motor with fuzzy control system. The research is useful for further controller design and practical application of the novel motor.

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Section: Fuzzy Control For Toroidal Motormentioning

confidence: 99%

Fuzzy Control for Dual-stator Toroidal Motor with Hybrid Excitation

Liu¹,

Wang²

2016

Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

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“…Defuzzifier is the inverse operation of the fuzzifier. It consists in transforming the linguistic variables into real or digital variables [11].…”

Section: Structure Of Fuzzy Logic Systemmentioning

confidence: 99%

A New Fuzzy Iterative Learning Control Algorithm for Single Joint Manipulator

Wang

Bian

2016

Archives of Control Sciences

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This paper present a new fuzzy iterative learning control design to solve the trajectory tracking problem and performing repetitive tasks for rigid robot manipulators. Several times' iterations are needed to make the system tracking error converge, especially in the first iteration without experience. In order to solve that problem, fuzzy control and iterative learning control are combined, where fuzzy control is used to tracking trajectory at the first learning period, and the output of fuzzy control is recorded as the initial control inputs of ILC. The new algorithm also adopts gain self-tuning by fuzzy control, in order to improve the convergence rate. Simulations illustrate the effectiveness and convergence of the new algorithm and advantages compared to traditional method.

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“…The DC link voltage is regulated using a PI controller which parameters are tuned based on the capacitor value and the dynamics of the regulation loop. 31,32 The reference active power injected to the electrical supply network is given by…”

Section: A DC Bus Voltage Model and Controlmentioning

confidence: 99%

Proposal of a new hybrid control strategy for dynamic performance improvement of wound field synchronous generator-based wind turbines

Tahir

Belfedal

Allaoui

et al. 2015

Journal of Renewable and Sustainable Energy

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A new hybrid control method for controlling back-to-back converter in permanent magnet synchronous generator wind turbines Control of a hybrid wind turbine/battery energy storage power generation system considering statistical wind characteristics J. Renewable Sustainable Energy 4, 053105 (2012); 10.1063/1.4751472Control strategies of doubly fed induction generator-based wind turbine system with new rotor current protection topology J. Renewable Sustainable Energy 4, 043123 (2012);This paper presents a simulation study of the control of a variable speed wind energy conversion system (WECS) using a wound field synchronous generator (WFSG). The proposed scheme is based on an RST controller with adaptive fuzzy gain scheduling (AFGS-RST) and regulates the active and reactive powers exchanged between the stator of the WFSG and the grid to ensure a Maximum Power Point Tracking of the WECS. The overall system model was implemented in MATLAB/Simulink with three different power controllers (the polynomial RST, the fuzzy logic controller, and the AFGS-RST controller). The performances of these controllers are evaluated under different operating conditions of the WECS power system. The results demonstrate that AFGS-RST controller is very effective in improving the power flow and very robust against variable transmission line parameters compared to the two other controllers. V C 2015 AIP Publishing LLC.

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Fuzzy logic control strategy of wind generator based on the dual-stator induction generator

Cited by 45 publications

References 12 publications

Fuzzy Control for Dual-stator Toroidal Motor with Hybrid Excitation

Fuzzy Control for Dual-stator Toroidal Motor with Hybrid Excitation

A New Fuzzy Iterative Learning Control Algorithm for Single Joint Manipulator

Proposal of a new hybrid control strategy for dynamic performance improvement of wound field synchronous generator-based wind turbines

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