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Input signals disturbances of controllers in a field-oriented control system with a slip-ring motor and their impact on rotational speed

Hudy W., Pytel K., Jaracz K.

Mining – Informatics, Automation and Electrical Engineering

2016

R. 54, nr 4

11--14 [tekst ang.], 56--60 [tekst pol.]

In the article the authors investigated a field-oriented control system with a slip-ring shaded-pole motor. Additive disturbing signals were introduced into input signals of the control system controllers. The rotational speed waveform was observed as an output of the system. Disturbing signals were sine-wave signals with known frequency. The field-oriented control system was parametrically optimized with the use of an evolutionary algorithm. The testing was carried out with the use of the MATLAB/Simulink software.

W ramach niniejszej pracy zbadano układ polowo-zorientowany z silnikiem pierścieniowym zwartym. Wprowadzano addytywne sygnały zakłócające do sygnałów wejściowych regulatorów tego układu sterowania. Obserwowano przebieg prędkości obrotowej, który był wyjściem układu. Sygnałami zakłócającymi były sygnały sinusoidalne o znanej częstotliwości. Układ FOC był zoptymalizowany parametrycznie przy wykorzystaniu algorytmu ewolucyjnego. Badania przeprowadzono metodą komputerową korzystając z oprogramowania MATLAB/Simulink.

On the Validity of the Noise Model of Quantization for the Frequency-Domain Amplitude Estimation of Low-Level Sine Waves

Bellan D.

Metrology and Measurement Systems

2015

Vol. 22, nr 1

89--100

This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter. This is a quite common condition for high-speed low-resolution converters. A digitized sine wave is transformed into the frequency domain through the discrete Fourier transform. The error in the amplitude estimate is treated as a random variable since the offset and the phase of the sine wave are usually unknown. Therefore, the estimate is characterized by its standard deviation. The proposed model evaluates properly such a standard deviation by treating the quantization with a Fourier series approach. On the other hand, it is shown that the conventional noise model of quantization would lead to a large underestimation of the error standard deviation. The effects of measurement parameters, such as the number of samples and a kind of the time window, are also investigated. Finally, a threshold for the additive noise is provided as the boundary for validity of the two quantization models.