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A Fuzzy Predictive Filter for Sinusoidal Signals with Time-Varying Frequencies
Authors: X. Z. Gao, S. J. Ovaska, X. Wang
Abstract:
Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085515
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[1] S. Väliviita and S. J. Ovaska, "Delayless method to generate current reference for active filters," IEEE Trans. on Industrial Electronics, vol. 45, no. 4, pp. 559-567, August 1998.
[2] O. Vainio and S. J. Ovaska, "Noise reduction in zero crossing detection by predictive digital filtering," IEEE Trans. on Industrial Electronics, vol. 42, no. 1, pp. 58-62, February 1995.
[3] O. Vainio and S. J. Ovaska, "Digital filtering for robust 50/60 Hz zero-crossing detectors," IEEE Trans. on Instrumentation and Measurement, vol. 45, no. 2, pp. 426-430, April 1996.
[4] R. E. Crochiere and L. R. Rabiner, Multirate Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1983.
[5] F. Russo, "Fuzzy systems in instrumentation: fuzzy signal processing," IEEE Trans. on Instrumentation and Measurement, vol. 45, no. 2, pp. 683-689, 1996.
[6] X. Z. Gao and S. J. Ovaska, "A new fuzzy filter with application in motion control systems," in Proc. IEEE International Conference on Systems, Man, and Cybernetics, Tokyo, Japan, October 1999, pp. 280-285.
[7] S. Väliviita, X. Z. Gao, and S. J. Ovaska, "Polynomial predictive filters: complementing technique to fuzzy filtering," in Proc. IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA, October 1998, pp. 4648-4652.
[8] M. Sugeno and G. T. Kang, "Structure identification of fuzzy model," Fuzzy Sets and Systems, vol. 28, no. 1, pp. 15-22, 1988.
[9] S. Haykin, Neural Networks, A Comprehensive Foundation. Second Edition, Upper Saddle River, NJ: Prentice-Hall, 1999.
[10] T. L. Leung, S. Väliviita, and S. J. Ovaska, "Adaptive and delayless filtering system for sinusoids with varying frequency," in Proc. IEEE SoutheastCon, Lexington, KY, March 1999, pp. 149-153.
[11] S. J. Ovaska and O. Vainio, "Evolutionary-programming-based optimization of reduced-rank adaptive filters for reference generation in active power filters," IEEE Trans. on Industrial Electronics, vol. 51, no. 4, pp. 910-916, 2004.
[12] O. Vainio and S. J. Ovaska, "General parameter-based adaptive extension to FIR filters," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, Salt Lake City, UT, May, 2001, pp. 3765-3768.