Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62280
Title: High robustness of an SR motor angle estimation algorithm using fuzzy predictive filters and heuristic knowledgebased rules
Authors: Cheok, A.D. 
Ertugrul, N.
Keywords: Adaptive filters
Error analysis
Fuzzy logic
Fuzzy systems
Nonlinear filters
Parameter estimation
Reluctance motor drives
Issue Date: Oct-1999
Source: Cheok, A.D.,Ertugrul, N. (1999-10). High robustness of an SR motor angle estimation algorithm using fuzzy predictive filters and heuristic knowledgebased rules. IEEE Transactions on Industrial Electronics 46 (5) : 904916-. ScholarBank@NUS Repository.
Abstract: In this paper, the operation of a fuzzy predictive filter used to provide high robustness against feedback signal noise in a fuzzy logic (FL)based angle estimation algorithm for the switched reluctance motor is described. The fuzzy predictive filtering method combines both FLbased timeseries prediction, as well as a heuristic knowledgebased algorithm to detect and discard feedback signal error. As it is predictive in nature, the scheme does not introduce any delay or phase shift in the feedback signals. In addition, the fuzzy predictive filter does not require any mathematical modeling of the noise and, therefore, can be used effectively to control nonGaussian impulsivetype noise. An analysis of the noise and error commonly found in practical motor drives is given, and how this can effect position estimation. It is shown using experimental results that the FLbased scheme can cope well with erroneous and noisy feedback signals. © 1999 IEEE.
Source Title: IEEE Transactions on Industrial Electronics
URI: http://scholarbank.nus.edu.sg/handle/10635/62280
ISSN: 02780046
Appears in Collections:Staff Publications

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