Mekatronik Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/255
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Article Citation - WoS: 2Citation - Scopus: 2Development of Air-To Engagement Analysis Model of Fighter Aircrafts(Gazi Univ, Fac Engineering Architecture, 2022) Bektas, Almila; Ergezer, Halit; Erdogan, SinemIn operational analysis studies; it is possible to model and simulate at an engineering level, engagement level, task level and campaign forces level. In this study, modelling and simulation studies are performed in engagement-level allowing the analysis of air-to-ground engagement effectiveness of fighter aircraft according to the operational environment. The operating environment of the combat aircraft, which provides survivability analysis based on low visibility and electronic mixing capabilities, is created. The search radar and tracking radar models for ground-to-air threats have been designed in accordance with the engagement level. The dynamic model of the fighter aircraft and the ground-to-air missile have been modelled using pseudo 5 degree-of-freedom. Modelling has been carried out to allow the use of changes in the Radar Crosssectional Area (RCS), which is one of the most important factors affecting the survivability of the aircraft, with respect to azimuth and elevation angles. The Radio Frequency (RF) jamming capability of the fighter aircraft has also been modelled in accordance with the engagement level. The results of the generic scenarios for the analysis of the effect of these models' parameters on the survivability of fighter aircraft have been presented.Article Citation - WoS: 4Citation - Scopus: 4Window Length Insensitive Real-Time Emg Hand Gesture Classification Using Entropy Calculated From Globally Parsed Histograms(Sage Publications Ltd, 2023) Alguner, Ayber Eray; Ergezer, HalitElectromyography (EMG) signal classification is vital to diagnose musculoskeletal abnormalities and control devices by motion intention detection. Machine learning assists both areas by classifying conditions or motion intentions. This paper proposes a novel window length insensitive EMG classification method utilizing the Entropy feature. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. Additionally, the entropy feature can classify feature vectors of different sliding window lengths without including them in the training data. Many kinds of entropy feature succeeded in electroencephalography (EEG) and electrocardiography (ECG) classification research. However, to the best of our knowledge, the Entropy Feature proposed by Shannon stays untested for EMG classification to this day. All the machine learning models are tested on datasets NinaPro DB5 and the newly collected SingleMyo. As an initial analysis to test the entropy feature, classic Machine Learning (ML) models are trained on the NinaPro DB5 dataset. This stage showed that except for the K Nearest Neighbor (kNN) with high inference time, Support Vector Machines (SVM) gave the best validation accuracy. Later, SVM models trained with feature vectors created by 1 s (200 samples) sliding windows are tested on feature vectors created by 250 ms (50 samples) to 1500 ms (300 samples) sliding windows. This experiment resulted in slight accuracy differences through changing window length, indicating that the Entropy feature is insensitive to this parameter. Lastly, Locally Parsed Histogram (LPH), typical in standard entropy functions, makes learning hard for ML methods. Globally Parsed Histogram (GPH) was proposed, and classification accuracy increased from 60.35% to 89.06% while window length insensitivity is preserved. This study shows that Shannon's entropy is a compelling feature with low window length sensitivity for EMG hand gesture classification. The effect of the GPH approach against an easy-to-make mistake LPH is shown. A real-time classification algorithm for the entropy features is tested on the newly created SingleMyo dataset.Article Citation - WoS: 2Citation - Scopus: 3Control Structure Design With Constraints for a Slung Load Quadrotor System(Sage Publications Ltd, 2024) Leblebicioglu, Kemal; Ergezer, HalitWe propose a control structure for a quadrotor carrying a slung load with swing-angle constraints. This quadrotor is supposed to pass through the waypoints at specified speeds. First, a cascaded PID autopilot is designed, which adaptively gives attention to position and speed requirements as a function of their errors. Its parameters are found from an optimization problem solved using the PSO algorithm. Second, this controller's performance is improved by adding the Complementary Controller employing an ANN. 5. Training data for the ANN is created by solving optimal control problems. The ANN is activated when the swing angle constraint is about to be violated. It is trained using optimal control values corresponding to the cases where the swing angle falls in a particular band about the upper swing angle constraint. Simulations are performed in a MATLAB environment. Finally, some of the simulation results are validated on a physical system.Article Citation - WoS: 7Citation - Scopus: 10Online Path Planning for Unmanned Aerial Vehicles To Maximize Instantaneous Information(Sage Publications inc, 2021) Leblebicioglu, Kemal; Ergezer, HalitIn this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate forbidden zones during a mission. Additionally, the significance and reliability of the information collected about a target are assumed to decrease with time. The proposed solution finds each vehicle's path by solving an optimization problem over a planning horizon while obeying specific rules. The basic structure in our solution is the centralized task assignment problem, and it produces near-optimal solutions. The solution can handle moving, pop-up targets, and UAV loss. It is a complicated optimization problem, and its solution is to be produced in a very short time. To simplify the optimization problem and obtain the solution in nearly real time, we have developed some rules. Among these rules, there is one that involves the kinematic constraints in the construction of paths. There is another which tackles the real-time decision-making problem using heuristics imitating human- like intelligence. Simulations are realized in MATLAB environment. The planning algorithm has been tested on various scenarios, and the results are presented.Article Citation - WoS: 1Citation - Scopus: 2Classification of Low Probability of Intercept Radar Waveforms Using Gabor Wavelets(Gazi Univ, Fac Engineering Architecture, 2021) Ergezer, HalitLow Probability of Intercept (LPI Radar) is a class of radar with specific technical characteristics that make it very difficult to intercept with electronic support systems and radar warning receivers. Because of their properties as low power, variable frequency, wide bandwidth, LPI radar waveforms are difficult to intercept by ESM systems. In recent years, studies on the classification of waveforms used by these types of radar have been accelerated. In this study, Time-Frequency Images (TFI) has been obtained from the LPI radars waveforms by using Choi-Williams Distribution method. From these images, feature vectors have been generated using Gabor Wavelet transform. In contrast to many methods in the literature, waveform classification has been performed by directly comparing the feature vectors obtained without using any machine learning method. With the method we propose, classification accuracies were obtained at intervals of 2 dB between -20 dB and 10 dB and performed at reasonable classification accuracy rates up to -8 dB SNR value. Better results than the best reported in the literature were obtained for some signal types. The results obtained for all waveform types are given in comparison with the results of the existing methods in the literature.Article Citation - WoS: 2Citation - Scopus: 4A New Systematic and Flexible Method for Developing Hierarchical Decision-Making Models(Tubitak Scientific & Technological Research Council Turkey, 2015) Beldek, Ulas; Leblebicioglu, Mehmet Kemal; Lebleb Iciog lu, Mehmet Kemal; Belde, UlaşThe common practice in multilevel decision-making (DM) systems is to achieve the final decision by going through a finite number of DM levels. In this study, a new multilevel DM model is proposed. This model is called the hierarchical DM (HDM) model and it is supposed to provide a flexible way of interaction and information flow between the consecutive levels that allows policy changes in DM procedures if necessary. In the model, in the early levels, there are primary agents that perform DM tasks. As the levels increase, the information associated with these agents is combined through suitable processes and agents with higher complexity are formed to carry out the DM tasks more elegantly. The HDM model is applied to the case study 'Fault degree classification in a 4-tank water circulation system'. For this case study, the processes that connect the lower levels to the higher levels are agent development processes where a special decision fusion technique is its integral part. This decision fusion technique combines the previous level's decisions and their performance indicator suitably to contribute to the improvement of new agents in higher levels. Additionally, the proposed agent development process provides flexibility both in the training and validation phases, and less computational effort is required in the training phase compared to a single-agent development simulation carried out for the same DM task under similar circumstances. Hence, the HDM model puts forward an enhanced performance compared to a single agent with a more sophisticated structure. Finally, model validation and efficiency in the presence of noise are also simulated. The adaptability of the agent development process due to the flexible structure of the model also accounts for improved performance, as seen in the results.Article Citation - WoS: 10Citation - Scopus: 9The Effect of Powder Mixed and Heated Dielectric on Drilling Performance of Electric Discharge Machining (Edm)(Gazi Univ, Fac Engineering Architecture, 2016) Cogun, Can; Urtekin, Levent; Ozerkan, H. Bekir; Uslan, Ibrahim; Erdem, OguzIn this study, heated silicon oil with added carbon and starch powders was used as dielectric liquid, instead of common hydro-carbon based dielectrics, to obtain better hole surface quality with rotating brass tube electrode in electric discharge machining (EDM). The electro-rheometer tests were conducted to find out the suitable temperature and powder concentration values of the electro-rheological (ER) dielectric under the electric field. Higher workpiece material removal rates (MRR) was obtained in carbon powder added dielectrics than the starch powder added ones for rotating and non-rotating electrodes. The optical microscope observations of the machined hole surfaces indicated that the carbon powder added dielectrics reduced the diameter and depth of the discharge craters, thereby resulting in uniformly distributed and round top peaked surface topography. The starch powder addition to the carbon mixed dielectric further improved the surface quality for both rotating and non-rotating electrodes cases at 30 degrees C and 75 degrees C dielectric temperatures.Article Citation - WoS: 2Investigation on the Influence of Parameter Uncertainties in the Position Tracking of Robot Manipulators(Univ North, 2019) Ghanbarpour Asl, Habib; Han, Kerim YoudeThis paper presents a novel trajectory tracking method for robot arms with uncertainties in parameters. The new controller applies the robust output feedback linearization method and is designed so that it is robust to the variation of parameters. Robustness of the algorithm is evaluated when the parameters of the system are floating over 10 percent up and down. An Unscented Kalman Filter (UKF) is applied for state and parameter estimation purposes. As the considered system has 8 unknown parameters while only 5 of them are independent parameters, UKF is applied only to the augmented system with independent parameters. Three types of simulations are applied depending on sensor groups - first with both position and joint sensors, second with only position sensors and third with only joint sensors. The observation of parameters in these groups is discussed. Simulation results show that when both position sensors and joint sensors are used, all the parameters and states are observable and good tracking performances are obtained. When only position sensors are used, the accuracy of the estimated parameters is reduced, and low tracking performances are revealed. Finally, when only joint sensors are applied, the lengths of robot arms are unobservable, but other parameters related to the dynamic system are observable, and poor tracking performances are given.