Browsing by Author "Nazlibilek, Sedat"

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Discrete Lissajous and Recton Functions: A New Method for Frequency Response Measurements
(2021) Nazlibilek, Sedat; Karacor, Deniz
An innovative and completely new technique so called discrete Lissajous functions and recton functions for signal analysis and measurement is explained. The contribution of the study is that it is a new digital method of obtaining information on frequency, change of frequency, phase and phase shift as well as auto-correlation, cross-correlation and energy functions of signals in digital form on-line that may be difficult to be provided in analog form and available for measurement and control applications at each sampling instance directly. The discrete Lissajous figures and recton functions can also be sketched in digital image form for further analysis of signals and systems. They are based on an algorithm utilizing discrete convolutions of discrete time signals. They can be depicted in 3D form. They give more information than classical analog Lissajous figures obtained on an oscilloscope screen. They can be used for several applications from chaotic systems to biomedical applications requiring to finding correlations, energies as well as frequency and phase information of the signals and controlling such systems. In this study, the application of them to systems steady-state, mainly frequency response analysis is explained after giving basic definitions.
GaN-based Single Stage Low Noise Amplifier for X-band Applications
(2022) Caglar, Gizem Tendurus; Aras, Yunus Erdem; Urfali, Emirhan; Yilmaz, Dogan; Ozbay, Ekmel; Nazlibilek, Sedat
Source degenerated HEMTs are used to achieve good noise matching and better input return loss without degrading the noise figure and reducing the stability. This work presents an MMIC design for the frequency band of 8 -11 GHz by using HEMTs with source degeneration in 0.15 mu m GaN on SiC technology. All design work is done in the Advanced Design System. The LNA delivers more than 6.9 dB gain with better than 8.5 dB and 9.5 dB input and output return losses, respectively. In addition, the gain ripple is around 2.7 dB. The noise figure of the amplifier is achieved below 1.1 dB with P1dB of 17.2 dBm and %12.7 drain efficiency within the operating bandwidth at the bias conditions of 9 V/20 mA.
Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning
(2021) Nazlibilek, Sedat; Ali, Issa; Askir, Alyaseh
Electrical power systems usually suffer from instabilities because of some disturbances occurring due to environmental conditions, system failures, and loading conditions. The most frequently encountered problem is the loss of synchronization between the rotor angle and the stator magnetic angle for synchronous generators. The contribution of this study is that a nonlinear adaptive control approach called feedback error learning (FEL) is utilized to improve the small-signal stabilities of an electric power system. The power system under study is composed of a synchronous machine connected to infinite bus. Many advantages of FEL control approach makes it capable to robustly adapting with all possible operating conditions rather than using optimization algorithms for tuning the conventional power system stabilizer (CPSS) that is still unsatisfactory especially at some critical operating points. The performances of two controllers, namely the proposed FEL scheme and the conventional controller CPSS, are tested by Matlab simulations. It is found that the FEL controller can be effectively used as an alternative stabilizer for improving small-signal stabilities of the power system.