Abstract
In recent years, three-phase boost rectifiers, due to their high efficiency, good current quality and low EMI emissions are widely used in industry as Power Factor Correction (PFC) converters. Performance criteria of these converters significantly improve with increasing the switching frequency, and highly depend on the control strategy used. This paper presents a novel approach to control of three phase boost rectifiers. The proposed method is a hybrid of wavelet and neural network (WNN). Simulation results show that this control strategy is very robust, flexible and also the response of the system is very fast. With applying WNN to the three-phase boost rectifier, the controlled system has unity power factor, sinusoidal input currents and regulated output voltage.
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© 2004 Springer-Verlag Berlin Heidelberg
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Rashidi, F., Rashidi, M. (2004). Design of a Robust and Adaptive Wavelet Neural Network for Control of Three Phase Boost Rectifiers. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_86
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DOI: https://doi.org/10.1007/978-3-540-30133-2_86
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23206-3
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