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

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.

3

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.

4

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.