Wyniki wyszukiwania - BazTech

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High performances of grid-connected DFIG based on direct power control with fixed switching frequency via MPPT strategy using MRAC and neuro-fuzzy control

Amrane F., Chaiba A., Mekhilef S.

Journal of Power Technologies

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2016

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Vol. 96, nr 1

27--39

EN

This paper presents high performance improved direct power control (DPC) based on model reference adaptive control (MRAC) and neuro-fuzzy control (NFC) for grid connected doubly fed induction generator (DFIG), to overcome the drawbacks of conventional DPC which was based only on PID controllers, namely the speed/efficiency trade-off and divergence from peak power under fast variation of wind speed. A mathematical model of DFIG implemented in the d-q reference frame is achieved. Then, a direct power control algorithm for controlling rotor currents of DFIG is incorporated using PID controllers, and space-vector modulation (SVM) is used to determine a fixed switching frequency. The condition of the stator side power factor is controlled at unity level via MPPT strategy. The MRAC which is based on DPC is investigated instead of PID regulators. Also, the performances of NFC based on DPC are tested and compared to those achieved using MRAC controller. The results obtained in the Matlab/Simulink environment using robustness tests show that the NFC is efficient, has superior dynamic performance and is more robust during parameter variations.

2

Implementation of a Neuro-Fuzzy Direct Torque and Reactive Power Control for Doubly Fed Induction Motor

Jacomini R. V., Rocha C. M., Altuna J. A. T., Azcue-Puma J. L., Capovilla C. E., Sguarezi Filho A. J.

Przegląd Elektrotechniczny

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2014

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R. 90, nr 10

179-187

EN

This paper proposes a Takagi-Sugeno neuro-fuzzy inference system for direct torque and stator reactive power control applied to a doubly fed induction motor. The control variables (d-axis and q-axis rotor voltages) are determined through a control system composed by a neuro-fuzzy inference system and a first order Takagi-Sugeno fuzzy logic controller. Experimental results are presented to validate the controller operation for variable speed under no-load and load conditions and stator reactive power variation under load condition. For this last validation, a PI controller is used to control the rotor speed, thereby its output is used to manipulate the torque in order to follow the demanded speed value.

XX

W artykule opisano inferencyjny neuro-fuzzy system Takagi-Sugeno użyty do sterowania momentem i mocą bierną w podwójnie zasilanym silniku indukcyjnym. Przeprowadzono eksperymenty sterowania silnikiem obciążonym i nieobciążonym.

3

Neuronowo-rozmyte systemy sterowania mobilnym robotem kołowym

Hendzel Z., Muszyńska M.

Modelowanie Inżynierskie

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2012

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T. 14, nr 45

58--63

PL

Celem niniejszej pracy było zbadanie możliwości zastosowania algorytmów neuronowo-rozmytych w sterowaniu w czasie rzeczywistym ruchem nadążnym mobilnego robota kołowego w obecności zmiennych warunków pracy oraz ich ocena dotycząca jakości sterowania.

EN

The aim of this study was to investigate the possibility of using neuro-fuzzy algorithms for control traffic in real-time mobile robot in the presence of variable working conditions and their assessment of the quality control.

4

Adaptive fuzzy control of a wheeled mobile robot

Hendzel Z., Muszyńska M.

International Journal of Applied Mechanics and Engineering

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2012

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Vol. 17, no. 3

827-835

EN

The objective of this paper was to investigate the possibility of using neuro-fuzzy algorithms in the real-time follower control system of a wheeled mobile robot in the presence of variable basic conditions of work and their assessment of the quality of control. For this purpose the intelligent servo motion controller was developed based on neural networks and fuzzy logic systems whose the task is to compensate the non-linearity and uncertain modeling of the mobile robot's traffic. This system has been designed in such a way as to allow for modification of its properties at any moment due to the changing working conditions of the mobile robot. The object of control is a two-wheeled mobile robot.

5

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator

Orłowska-Kowalska T., Dybkowski M.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2012

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Vol. 60, nr 1

61-70

EN

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct rotor-field oriented control (DRFOC) of the induction motor (IM) drive structure. Connective weights of the controller are trained on-line according to the error between the actual speed of the drive and the reference model output signal. The rotor flux and speed of the vector controlled induction motor are estimated using the model reference adaptive system (MRAS) – type estimator. Presented simulation results are verified by experimental tests performed on the laboratory-rig with DSP controller.

6

Neuro-fuzzy control design of processes in chemical technologies

Blahová L., Dvoran J., Kmeťová J.

Archives of Control Sciences

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2012

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Vol. 22, no. 2

233-250

EN

The paper presents design of neuro-fuzzy control and its application in chemical technologies. Our approach to neuro-fuzzy control is a combination of the neural predictive controller and the neuro-fuzzy controller (Adaptive Network-based Fuzzy Inference System - ANFIS). These controllers work in parallel. The output of ANFIS adjusts the output of the neural predictive controller to enhance the control performance. Such design of an intelligent control system is applied to control of the continuous stirred tank reactor and laboratory mixing process.

7

The application of the neuro - fuzzy controller in the power transmission system with the DC motor and variable parameters

Łukowski R.

Poznan University of Technology Academic Journals. Electrical Engineering

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2011

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No. 65

97--104

EN

The paper presents the algorithm of the control of speed of the separately excited DC the first zone. The cascade arrangement of the control of the angular speed was the algorithm of steering with the regulator of the speed and the regulator of the current. The comparative analysis of the DC motor control system with variable moment of interia and the use of classic PI and neuro-fuzzy controllers were conducted.