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Öğe Adaptive gradient descent control of stable, first order, time-delay dynamic systems according to time-varying fir filter model assumption(Institute of Electrical and Electronics Engineers Inc., 2019) Yagmur N.; Alagoz B.B.This study investigates robust control performance of adaptive gradient descent control in case of parametric perturbation of first order stable LTI systems. The proposed adaptive gradient descent control method is a variant of direct gradient descent control. The study aims to implement an adaptive control scheme for modeling-free control of stable, first-order, time delay plant models. The method implements two gradient descent optimizers. The first one performs only for synthesis of control signal, and the second optimizer works for a short-Time model prediction based on instant input-output relation of a plant. We use a time-varying finite impulse response (TV-FIR) form to approximate short-Term input-output relations of a first order stable plant dynamics and this work is an extended version of adaptive gradient descent control schemes that were presented in [6] and [7]. Adaptation and control laws are derived for this FIR model premise according to gradient descent method. The robust control performance of the proposed control method is investigated according to simulation results and compared with performance of optimal PI controller designs. © 2019 IEEE.Öğe Analogue Implementation of a Fractional-PI? Controller for DC Motor Speed Control(Institute of Electrical and Electronics Engineers Inc., 2019) Herencsar N.; Kartci A.; Koton J.; Sotner R.; Alagoz B.B.; Yeroglu C.In this paper, an approach to design a fractional-order integral operator s where -1 < ?< 0, using an analogue technique, is presented. The integrator with a constant phase angle -80.1 degree (i.e. order ? = -0.89), bandwidth greater than 3 decades, and maximum relative phase error 1.38% is designed by cascade connection of first-order bilinear transfer segments and first-order low-pass filter. The performance of suggested realization is demonstrated in a fractional-order proportional-integral (FOPI) controller described with proportional constant 1.37 and integration constant 2.28. The design specification corresponds to a speed control system of an armature controlled DC motor, which is often used in mechatronic and other fields of control theory. The behavior of both proposed analogue circuits employing two-stage Op-Amps is confirmed by SPICE simulations using TSMC 0.18 ?m level-7 LO EPI SCN018 CMOS process parameters with ±0.9 V supply voltages. © 2019 IEEE.Öğe A Computational Intelligent Analysis Scheme for Optimal Engine Behavior by Using Artificial Neural Network Learning Models and Harris Hawk Optimization(Institute of Electrical and Electronics Engineers Inc., 2021) Simsek O.I.; Alagoz B.B.Application of computational intelligence methods in data analysis and optimization problems can allow feasible and optimal solutions of complicated engineering problems. This study demonstrates an intelligent analysis scheme for determination of optimal operating condition of an internal combustion engine. For this purpose, an artificial neural network learning model is used to represent engine behavior based on engine data, and a metaheuristic optimization method is implemented to figure out optimal operating states of the engine according to the neural network learning model. This data analysis scheme is used for adjustment of optimal engine speed and fuel rate parameters to provide a maximum torque under Nitrous oxide emission constraint. Harris hawks optimization method is implemented to solve the proposed optimization problem. The solution of this optimization problem addresses eco-friendly enhancement of vehicle performance. Results indicate that this computational intelligent analysis scheme can find optimal operating regimes of an engine. © 2021 IEEE.Öğe Daily Forecasting of Demand Orders with Optimal Architecture Artificial Neural Network Learning Models(Institute of Electrical and Electronics Engineers Inc., 2021) Simsek O.I.; Alagoz B.B.In recent years, with the increase in volume of buying orders, demand forecast based on the order data is important for improvement of production, distribution and selling services. For this reason, the predictability of orders will increase efficiency in many areas by timely delivering orders, increasing earnings, and customer satisfaction in trading. This article aims to estimate total amount of daily orders by using an optimal structured artificial neural network learning model. To optimize rectangular architecture of artificial neural network model, a metaheuristic optimization, which determines the number of hidden layers and number of neurons, is used. In the study, training of neural networks was carried out with the Levenberg-Marquardt backpropagation algorithm for daily orders collected for 60 days. During this training, the network's layer and neuron number were optimized with a gray wolf optimization algorithm. Results indicate that optimal architecture neural network can better estimate total daily demand orders. © 2021 IEEE.Öğe Detection of RR interval alterations in ECG signals by using first order fractional filter(Institute of Electrical and Electronics Engineers Inc., 2016) Alagoz B.B.; Yeroglu C.; Kavuran G.; Ates A.Sleep apnea syndrome deteriorates sleeping quality and daily performance of many individuals. This study presents utilization of fractional-order low pass filtering for the detection of RR interval alteration from electrocardiogram (ECG) signals. In the case of sleeping apnea, cardiac interbeat intervals prolong and it is viewed as an indication of obstructive sleep apnea state. The prolonged interbeat intervals manifest themselves as the decrease of R peak frequency (increase of RR intervals) in ECG signals. It results in shifting of spectral components composing R peaks towards lower frequencies in energy signal of ECG. In order to detect prolonging interbeat intervals, energy signal calculated from ECG is applied to low-pass fractional-order filter. Transition band of the low-pass filter is used as a ramp filter in order to detect frequency variations in the energy of R peaks. We compare results of the first order fractional-order and integer order low-pass filters and demonstrate that the fractional-order filter can improve the detection performance of low-pass filtering by modifying transition band slope of low-pass filters. © 2016 IEEE.Öğe Disturbance rejection fopid control of rotor by multi-objective bb-bc optimization algorithm(American Society of Mechanical Engineers (ASME), 2017) Ates A.; Alagoz B.B.; Yeroglu C.; Yuan J.; Chen Y.This paper presents a FOPID tuning method for disturbance reject control by using multi-objective BB-BC optimization algorithm. Proposed method allows multi-objective optimization of set-point performance and disturbance rejection performances of FOPID control system. The objective function to be minimized is composed of the weighted sum of MSE for set-point performance and RDR for disturbance rejection improvement. The proposed optimization performs maximization of RDR and minimization of MSE and it can deal with the tradeoff between RDR performance and step-point performance. Application of the method is shown for autotuning of FOPID controller that is employed for control of TRMS model. We observed that low-frequency RDR indices can be used to improve disturbance rejection performance in multi-objective controller tuning problems. Particularly, for flight control application, disturbance reject control is very substantial to robust performance of propulsion systems. © Copyright 2017 ASME.Öğe Effects of fractional order integration on ASDM signals(Springer Berlin Heidelberg, 2017) Kavuran G.; Yeroğlu C.; Ateş A.; Alagoz B.B.Pulse density modulation (PDM) can find applications in consumer electronics, power and switch control systems. PDM signals can be generated by asynchronous sigma delta modulator (ASDM) structures and improvement of ASDM performance provides significant contribution for practical applications. This study numerically investigates effects of fractional order integration (FOI) on the PDM signal, produced by ASDM. We implemented fractional order integratorin ASDM structure and present numerical analysis to discuss effects of fractional order integrator on PDM signals, obtained for bipolar digital signal transmission application. Theoretical analysis indicates that FOI provides finer pulse trains and thus improves representation of original signal. In simulations, we tested FOI for various fractional-order values. Signal to noise ratio and signal to noise and distortion ratio (SINAD) levels of demodulated signals are reported for sinusoidal and audio test signals. Simulation results demonstrate that FOI can improve SNR and SINAD performance of ASDMs. © 2016, Springer-Verlag Berlin Heidelberg.Öğe Frequency deviation indicators for estimation of energy balance state in smart AC grids(Institute of Electrical and Electronics Engineers Inc., 2016) Alagoz B.B.; Keles C.; Kaygusuz A.; Akcin M.Due to increasing intermittent renewable energy utilization in smart grids, smart management of energy balance is becoming major concern of research studies. In the case of highly volatile generation and demand conditions, it is very important to estimate instant energy balance state of electricity grid to preserve energy balance automatically and avoid from the cases of generation deficiency and overloading. The utility frequency deviation is commonly used to restore power imbalance in AC grids. This study gives a discussion on the utilization of frequency deviation of AC power system as an indicator of energy balance state in smart grids. We consider two approaches to estimate instant AC frequency deviation of power systems under serious harmonic and noise conditions. The first one is based on frequency to amplitude conversion technique, which use band-pass ramp filtering of AC signal. The other method is based on the sinusoidal to pulse waveform conversion, and it uses measurement of pulse periods of the resulting square waveforms. We compare these two methods and discuss their advantages and disadvantages to generate a balance error signal for smart grid applications. A brief discussion on application of these signals for smart grid energy management is given. © 2016 IEEE.Öğe A Genetic Programming Based Pollutant Concentration Predictor Design for Urban Pollution Monitoring Based on Multi-Sensor Electronic Nose(Institute of Electrical and Electronics Engineers Inc., 2021) Ari D.; Alagoz B.B.An important part of air pollution control is the pollution monitoring. Since industrial spectrometers are expensive equipment, the number of observation points to monitor air pollution over an urban area can be limited. The low-cost multi-sensors network can spread over areas and form a wide-area electronic nose to estimate pollutant concentration distributions. However, the collected multisensor data should be analyzed to correctly estimate pollutant concentrations. This study demonstrates implementation of genetic programming (GP) to obtain prediction models that can estimate CO and NO2 concentrations from multisensor electronic nose data. For this purpose, to function as an electronic nose, a regression model from a training data set is obtained by using a tree-based GP algorithm. In order to improve performance of the GP based prediction models, data normalization is performed and prediction performance enhancements are demonstrated via statistical performance analyses on a test data set. © 2021 IEEE.Öğe Genetik algoritma ile düşük duyarlili?a sahip optimal fopid denetleyici tasarimi(Institute of Electrical and Electronics Engineers Inc., 2019) Tufenkci S.; Senol B.; Alagoz B.B.Researchers have demonstrated that Fractionalorder Proportional Integral Derivative (FOPID) controllers can provide superior control performance compared to classical PID controllers. This study presents an optimal FOPID controller design method in v-domain to achieve lower sensitivity to disturbance. For this purpose, an optimal FOPID controller design method is proposed, where a multi-objective optimization problem, which reduces sensitivity of system to external disturbances and stabilizes the system, is defined and solved by Genetic Algorithm (GA). This design is performed in the stability region of the first Riemann Sheet in v-plane. To increase system robustness against disturbances, sensitivity function of the system is minimized. Hence, a multi-objective optimization problem, which is solved by GA algorithm, is stated for placement of minimum angle system pole to a target angle within the stability region and minimization of system sensitivity function. Thus, for fractional order systems, FOPID controller design can be performed in v-domain. An illustrative design example and comparison of the resulting design with other design methods are presented. © 2019 IEEE.Öğe Modeling Daily Financial Market Data by Using Tree-Based Genetic Programming(Institute of Electrical and Electronics Engineers Inc., 2021) Ari D.; Alagoz B.B.A behavioral modeling of financial markets based on daily data is not an easy problem for machine learning algorithms. The social and physiological factors can take effect on market data and result in significant uncertainty in data. This study demonstrates an implementation of tree-based genetic programming (GP) to develop a mathematical model of stock market from the daily stock data of other stock markets to observe relations between global market trends and to consider this effect in market prediction problems. To obtain a prediction model of Istanbul Stock Exchange 100 Index (ISE100), numerical data from ISE100 and seven other international stock market indices are used to produce GP models that can estimate daily price changes in ISE100 according to daily change in other international stock market indices. To reduce negative effects of the data uncertainty on the GP modeling, ensemble average GP modeling performances are investigated and the results are reported for future research direction suggestions. © 2021 IEEE.Öğe Monte Carlo simulation-based planning method for overload safe electrical power systems(Universitatea Politehnica din Timisoara, 2014) Kaygusuz A.; Alagoz B.B.; Akcin M.; Keles C.; Karabiber A.; Gul O.Operational reliability of power systems is one of the most important concerns that engineers have when planning a secure and economical electrical power system. This paper presents a probabilistic power flow analysis, based on the Monte Carlo simulation method, to support an overload safe power system designed to tolerate demand uncertainty and fluctuations of transmission parameters. Generation and transmission capacities in the power system can be estimated on the basis of operational risks and system installation costs. The proposed approach will be very useful for the rational planning of secure power distribution systems.Öğe A note on robust stability analysis of fractional order interval systems by minimum argument vertex and edge polynomials(Institute of Electrical and Electronics Engineers Inc., 2016) Alagoz B.B.By using power mapping, stability analysis of fractional order polynomials was simplified to the stability analysis of expanded degree integer order polynomials in the first Riemann sheet. However, more investigation is needed for revealing properties of power mapping and demonstration of conformity of Hurwitz stability under power mapping of fractional order characteristic polynomials. Contributions of this study have two folds: Firstly, this paper demonstrates conservation of root argument and magnitude relations under power mapping of characteristic polynomials and thus substantiates validity of Hurwitz stability under power mapping of fractional order characteristic polynomials. This also ensures implications of edge theorem for fractional order interval systems. Secondly, in control engineering point of view, numerical robust stability analysis approaches based on the consideration of minimum argument roots of edge and vertex polynomials are presented. For the computer-aided design of fractional order interval control systems, the minimum argument root principle is applied for a finite set of edge and vertex polynomials, which are sampled from parametric uncertainty box. Several illustrative examples are presented to discuss effectiveness of these approaches. © 2014 Chinese Association of Automation.Öğe A photovoltaic system model for Matlab/Simulink simulations(2013) Keles C.; Alagoz B.B.; Akcin M.; Kaygusuz A.; Karabiber A.Solar energy maintains life on the earth and it is an infinite source of clean energy. There is an increasing trend for the use of solar cells in industry and domestic appliances because solar energy is expected to play significant role in future smart grids as a distributed renewable source. Optimal and large-scale integration of renewable sources into smart grid is possible by the aid of computer simulations and hence there is a growing demand for computer modeling and simulation of renewable sources. This study presents a generalized photovoltaic (PV) system simulation model for Matlab/Simulink simulation environment. The proposed model is based on a behavioral cell model for modeling solar radiance to electricity conversion and an electrical driver interface for implementing electrical characteristic of power limited systems in power simulations. The model is efficient in computational complexity and it is easy to configure for representing wide-range of PV installations. © 2013 IEEE.Öğe Sigmoid based PID controller implementation for rotor control(Institute of Electrical and Electronics Engineers Inc., 2015) Ates A.; Alagoz B.B.; Yeroglu C.; Alisoy H.This paper presents a sigmoid based variable coefficient PID (SBVC-PID) controller design for Twin Rotor MIMO System (TRMS). The proposed SBVC-PID controller dynamically changes controller coefficients according to a modified sigmoid function of the error signal. The modified sigmoid function is used to limit variability of PID controller coefficients in a predefined range. In the proposed method, each parameters of PID, namely pk, kt and kd, alter between predefined upper and lower bounds. A modified sigmoid function adjusted by a transition coefficient is used to alter each of the PID parameters between these bound limits. The variable coefficients of SBVC-PID maintain a hypercube in kp, kt and kd parameter space satisfying robust stability of the system. Well-known Kharitonov polynomials are used to ensure that the SBVC-PID coefficient alteration takes place in the robust stability intervals. Due to dynamically change of PID coefficients depending on magnitude of error signal, the control performance can be improved compared to conventional PID control. Performance of SBVC-PID controller is demonstrated via theoretical examples and TRMS rotor control simulations. © 2015 EUCA.Öğe Theoretical demonstration of the hybrid focusing points of sonic crystal flat lenses and possible applications(2013) Alagoz S.; Alagoz B.B.We demonstrate the hybrid focusing points of sonic crystals for a multi-source array applied to flat sonic crystal lenses. The contributions of different point source couples form hybrid focusing points. Ray-trace analyses are conducted for acoustic flat lenses with multi-source configurations. The finite-difference time-domain (FDTD) simulation of flat lenses with multi-source configurations demonstrates the establishment of pure and hybrid focusing points in a pyramidal constellation. The number of focusing points in the pyramidal constellation depends on the number of point sources. We propose an acoustic device for fine-tuning the location of a far-field hybrid focusing point and discuss its benefits for acoustic energy focusing application. © 2013 Chinese Physical Society and IOP Publishing Ltd.Öğe A theoretical investigation on consideration of initial conditions in fractional-order transfer function modeling(Institute of Electrical and Electronics Engineers Inc., 2017) Alagoz B.B.; Tepljakov A.; Petlenkov E.; Yeroglu C.This paper presents an investigation on contributions of initial condition consideration to fractional-order transfer functions in modeling linear time invariant systems. In this theoretical study, firstly, initial conditions are considered for fractional-order transfer function modeling in s-domain, and then impacts of initial conditions on model dynamics are discussed. An illustrative example is also presented to evaluate theoretical findings. © 2017 IEEE.Öğe Two dimension simulation of chest wall hyperthermia(2012) Barlaz Us S.; Alisoy H.Z.; Alagoz B.B.One of the cancer treatment methods is hyperthermia. In this study, by using cross section computer tomography (CSCT) of chest wall which the patient has been treated with radiotherapy for the single-source was placed into (internally) and out (externally) of the chest wall. SAR (Spesific Absorbtion Rate) distribution on the chest wall is numerically calculated by using finite difference time domain (FDTD) based electromagnetic wave propagation simulation. © Sila Science.Öğe Unitary fractional-order derivative operators for quantum computation(Elsevier, 2021) Alagoz B.B.; Alagoz S.Along with recent progresses in quantum computation technologies, researchers have addressed practical computational supremacies of quantum computers. The research works in the quantum computation domain mainly focus on progressive quantum algorithms and circuits in order to cope with computationally expensive engineering problems. This study aims to introduce possible implications of fractional calculus in quantum computation practice. In this perspective, a unitary fractional-order derivative operator family, which can be implemented by using phase operators, is defined and their possible utilizations for modeling and controlling quantum circuits are discussed. Moreover, the study demonstrates that the fractional derivative order can be used for controlling Shannon entropy of measurement probability distribution of qubits. Operation modes of single-sided and double-sided quantum interference circuits are analyzed, and optimal design of quantum interference circuits to obtain target probability distributions is investigated by using a genetic algorithm. This groundwork is helpful to extend topics of fractional calculus to quantum fractional calculus. © 2022 Elsevier Inc. All rights reserved.Öğe Value Set-Based Numerical Analysis of Robust Stability for Fractional-Order Retarded Quasi-Polynomials with Uncertain Parameters and Uncertain Fractional Orders(Springer Science and Business Media Deutschland GmbH, 2021) Matuš? R.; Senol B.; Alagoz B.B.; Ates A.This example-oriented contribution deals with the value set-based numerical analysis of robust stability for the family of fractional-order retarded quasi-polynomials with both uncertain parameters and uncertain fractional orders. The specific investigated feedback control system consists of the fractional-order PID controller and the controlled plant, represented by a heat transfer process described by the linear time-invariant fractional-order time-delay model with parametric uncertainty (with three uncertain parameters, namely, gain, fractional time constant, and fractional time-delay term, and furthermore two fractional orders). The graphical robust stability analysis is based on the numerical calculation of the value sets and the application of the zero exclusion principle. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
