Speaker-Independent Malay Syllable Recognition Using Singular and Modular Neural Networks
DOI:
https://doi.org/10.11113/jt.v35.611Abstract
This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.Downloads
Published
2012-01-20
Issue
Section
Science and Engineering
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
How to Cite
Speaker-Independent Malay Syllable Recognition Using Singular and Modular Neural Networks. (2012). Jurnal Teknologi (Sciences & Engineering), 35(1), 65–76. https://doi.org/10.11113/jt.v35.611