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    Disturbance rejection performance analyses of closed loop control systems by reference to disturbance ratio
    (Elsevier Science Inc, 2015) Alagoz, Bans Baykant; Deniz, Furkan Nur; Keles, Cemal; Tan, Nusret
    This study investigates disturbance rejection capacity of closed loop control systems by means of reference to disturbance ratio (RDR). The RDR analysis calculates the ratio of reference signal energy to disturbance signal energy at the system output and provides a quantitative evaluation of disturbance rejection performance of control systems on the bases of communication channel limitations. Essentially, RDR provides a straightforward analytical method for the comparison and improvement of implicit disturbance rejection capacity of closed loop control systems. Theoretical analyses demonstrate us that RDR of the negative feedback closed loop control systems are determined by energy spectral density of controller transfer function. In this manner, authors derived design criteria for specifications of disturbance rejection performances of PID and fractional order PID (FOPID) controller structures. RDR spectra are calculated for investigation of frequency dependence of disturbance rejection capacity and spectral RDR analyses are carried out for PID and FOPID controllers. For the validation of theoretical results, simulation examples are presented. (C) 2014 ISA. Published by Elsevier Ltd. All rights reserved.
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    Fractional Order Model Identification of Receptor-Ligand Complexes Formation by Equivalent Electrical Circuit Modeling
    (Ieee, 2019) Ates, Abdullah; Alagoz, Bans Baykant; Tepljakov, Aleksei; Petlenkov, Eduard; Yeroglu, Celaledddin; Kuznetsov, Aleksei; Sobolev, Innokenti
    In this study, relevant time resolved kinetic system is modeled according to linear fractional order model structure under the electrical circuit model assumption. The data, which were obtained from receptor ligand, are very noisy. Particularly, the unstable flowing of liquids around surfaces leads to irregular mass-transfer between the layers of reagent near the surface. Current flow of equivalent electric circuit modeling resembles overall mass flow and accumulation on surface corresponds to charge collection in capacitance. Thus, the charging and discharging process of fractional order capacitor can be used to represent accumulation and relaxation mechanisms of the receptor ligand complexes formation by using Stochastic Multi-parameter Divergence Optimization (SMDO) method. Meanwhile, error function that is comparison between model output with real output is used as an objective function for optimization of the fractional order model parameters.
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    Power Converters Modeling in Matlab/Simulink for Microgrid Simulations
    (Ieee, 2016) Karabiber, Abdulkerim; Keles, Cemal; Kaygusuz, Asim; Alagoz, Bans Baykant; Akcin, Murat
    Smart grid is a developing field for energy researchers. It offers technological improvements to have more controllable, reliable and sustainable power grids. Especially, the decreasing trend of fuels has pressurized to pay researchers' attention to renewable energy sources such as solar systems and wind turbines. The renewable energy sources generate electric power in different characteristics. Therefore, power converters are needed to integrate these sources in a grid to provide power flows among the sources and loads. This study presents Matlab/Simulink models of power converters and dynamic load structure, which are useful for smart grid simulations. These simulations can be used for research and educational purposes. Characteristic parameters of the models are suitable for existing devices. For power converters, Pulse-width Modulation technique is utilized that it is widely used in industry. The designed power converters and dynamic load models are tested in a microgrid application. The simulation results show that the designed power components are useful for smart grid simulation studies.
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    Probabilistic Relational Connectivity Analysis of Bigram Models
    (Ieee, 2019) Alnahas, Dima; Alagoz, Bans Baykant
    This study demonstrates an application of probabilistic relational graph connectivity analysis in bigram models (2-gram) of texts. The probabilistic relation matrices are calculated by estimating bigram co-occurrence probabilities in word sequence of a given short text. Then, deeper probabilistic connectivity relations among word sequences can be considered by calculating powers of probabilistic relation matrix of bigram models. Cosine similarity measure is used to evaluate similarity of probabilistic connectivity patterns of lexemes in a given message. Illustrative analysis examples are presented to discuss results of sentence-wise and short text analyses.