Mekatronik Mühendisliği Bölümü

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A comparison of iterative Fourier transform algorithms for image quality estimation
(2018) Alsaka, Dina Yaqoob; Arpali, Çağlar; Arpali, Serap Altay; 20809
A comparison was established between two iterative Fourier transform algorithms (IFTAs), such as the original Gerchberg–Saxton (GS) and the mixed-region amplitude freedom (MRAF) algorithms, for the hologram reconstruction of different target images through the full reference image quality estimation (IQE) and pixel homogeneity in the Fourier plane presented theoretically and experimentally. The comparison was applied depending upon both algorithms based on a computer-generated hologram (CGH) implemented utilizing a reflective phase-modulated liquid-crystal spatial light modulator (LC-SLM) to obtain the digital kinoform holograms of the desired intensity distributions. These digital holograms were applied to reconstruct the intensity patterns for 852 nm, which represents a laser beam source. The theoretical and experimental results of the reconstructed patterns obtained using the MRAF algorithm were found to be smoother and better than the patterns obtained using the GS algorithm. Unmodulated light beam (dc term) is removed from the reconstructed patterns attributed to digital kinoform holograms of MRAF algorithm as an alternative to the theoretical and experimental results without using any additional optic equipment at the light path. Moreover, this paper discussed the full reference objective quality estimations, such as mean square error (MSE), peak signal-to-noise ratio (PSNR), structural content (SC), normalized absolute error (NAE), normalized cross correlation (NK), and homogeneity of pixels, through the contrast (Cont) and inverse difference moment (IDM) for numerical and experimental results. According to the two desired intensity distributions processed theoretically and experimentally, the results of MRAF algorithm were found to be in the highly accurate recovered phase, the quality of image was enhanced, and the dc term was decreased. Image quality estimation of full reference objective relay on the feedback algorithms experimental attestation has not been implemented yet.
A configurable CAN FD controller: architecture and implementation
(IEEE, 2017) Afşin, Mehmet Ertuğ; Schmidt, Klaus Werner; Schmidt, Ece Güran
CAN FD is a new standard which provides fast. data rate while preserving the compatibility with CAN (controller area network). In this paper, a Configurable IP core architecture (A-CAN) which is compatible with the CAN FD standard, is proposed. Different than existing CAN/CAN FD controllers, the numbers and sizes of transmit and receive buffers of A-CAN can be configured in run time. To this end, A-CAN enables the best use of single controller hardware for different applications and enables improving the real time communication performance. A CAN communicates with the host device over SPI without any specific interface requirements. A-CAN is implemented on an FPGA Evaluation Board and its functionally is verified at a rate of 2 Mbps.
A new multi-agent decision making structure and application to model-based fault diagnosis problem
(IEEE, 2017) Leblebicioğlu, Kemal; Zengin, Yasin; Schmidt, Klaus Werner
A new hierarchical multi-agent decision-making structure has been proposed. There are two phases of the structure. The first phase is the construction phase where the decision making structure consisting of switching and classification agents is built on the training data set generated by the system scenarios. In construction phase, switching and classification agents are trained and made ready for decision making. In the decision phase, which is the second phase, the class of the new data sample is decided. This process is carried out by the transmission of the data sample to the correct classifier agent by the switching agents and the classification by the classifier agent. The proposed structure is applied to a complex fault identification problem and a successful result is obtained. The structure is also adaptable to other big data decision making problems.
Citation - WoS: 1
Citation - Scopus: 3
Analytical Solution of Thermal Stresses in a Functionally Graded Solid Cylinder Within Parabolic Continuous Grading
(Trans Tech Publications Ltd, 2013) Gulgec, Mufit; Ozturk, Ali; 4168
This paper presents analytical solutions of the thermal stresses in a functionally graded solid cylinder with fixed ends in elastic region. These thermal stresses are due to the uniform heat generation inside the cylinder. Material properties of the functionally graded (FG) cylinder vary radially according to a parabolic form. The material properties are assumed to be independent of the temperature which are yield strength, elasticity modulus, thermal conduction coefficient, thermal expansion coefficient and Poisson's ratio. The solutions for the thermal stresses are valid for both homogeneous and functionally graded materials.
Citation - Scopus: 12
Applied Supervisory Control for a Flexible Manufacturing System
(IFAC Secretariat, 2010) Moor, T.; Schmidt, K.; Perk, S.
This paper presents a case study in the design and implementation of a discrete event system (DES) of real-world complexity. Our DES plant is a flexible manufacturing system (FMS) laboratory model that consists of 29 interacting components and is controlled via 107 digital signals. Regarding controller design, we apply a hierarchical and decentralised synthesis method from earlier work in order to achieve nonblocking and safe closed-loop behaviour. Regarding implementation, we discuss how digital signals translate to discrete events from a practical point of view, including timing issues. The paper demonstrates how both, design and implementation, are supported by the open-source software tool libFAUDES.
Citation - WoS: 12
Citation - Scopus: 12
Averaging of Receiver Aperture for Flat-Topped Incidence
(Elsevier Sci Ltd, 2013) Kamacioglu, Canan; Baykal, Yahya; Yazgan, Erdem; 7812
Using a flat-topped profile for the incident beam, the power scintillation index for weak atmospheric turbulence is formulated and analytically evaluated. Through the use of the aperture averaging factor, the averaging effect of the finite receiver aperture on the intensity fluctuations for a flat-topped incident beam is examined. The influence of the order of flatness on the averaging is investigated. At large propagation lengths, increasing the flatness parameter decreases the power scintillations and it is possible to further reduce the scintillation by increasing the receiver aperture. Increasing the structure constant increases this effect. (C) 2013 Elsevier Ltd. All rights reserved.
Citation - WoS: 20
Citation - Scopus: 21
A Comparison of Iterative Fourier Transform Algorithms for Image Quality Estimation
(Optical Soc Japan, 2018) Alsaka, Dina Yaqoob; Arpali, Caglar; Arpali, Serap Altay; 20809
A comparison was established between two iterative Fourier transform algorithms (IFTAs), such as the original Gerchberg-Saxton (GS) and the mixed-region amplitude freedom (MRAF) algorithms, for the hologram reconstruction of different target images through the full reference image quality estimation (IQE) and pixel homogeneity in the Fourier plane presented theoretically and experimentally. The comparison was applied depending upon both algorithms based on a computer-generated hologram (CGH) implemented utilizing a reflective phase-modulated liquid-crystal spatial light modulator (LC-SLM) to obtain the digital kinoform holograms of the desired intensity distributions. These digital holograms were applied to reconstruct the intensity patterns for 852 nm, which represents a laser beam source. The theoretical and experimental results of the reconstructed patterns obtained using the MRAF algorithm were found to be smoother and better than the patterns obtained using the GS algorithm. Unmodulated light beam (dc term) is removed from the reconstructed patterns attributed to digital kinoform holograms of MRAF algorithm as an alternative to the theoretical and experimental results without using any additional optic equipment at the light path. Moreover, this paper discussed the full reference objective quality estimations, such as mean square error (MSE), peak signal-to-noise ratio (PSNR), structural content (SC), normalized absolute error (NAE), normalized cross correlation (NK), and homogeneity of pixels, through the contrast (Cont) and inverse difference moment (IDM) for numerical and experimental results. According to the two desired intensity distributions processed theoretically and experimentally, the results of MRAF algorithm were found to be in the highly accurate recovered phase, the quality of image was enhanced, and the dc term was decreased. Image quality estimation of full reference objective relay on the feedback algorithms experimental attestation has not been implemented yet.
Comprehensive Comparison of Various Machine Learning Algorithms for Rf Fingerprints Classification
(Institute of Electrical and Electronics Engineers Inc., 2023) Ergezer, H.; Gundogan, B.; 293396
In these days, the use of drones has become quite common. Remote controls can do the control of these drones with RF signals. It is important to prevent security vulnerabilities caused by using drones in our daily lives. A complex dataset was created by extracting the characteristics of the RF signals and preprocessing them. To solve this complex data set and problem, the application of models including Support Vector Machine (SVM), Random Forest, Decision Tree, Gradient Boosting, XGBoost and Neural Network (NN) models, including various ML models and comparison of optimization studies of these applied models are examined in this article. In addition, a wide range of studies was carried out to compare ML models, including comparison metrics such as Accuracy, Precision, Recall, Mean Squared Error (MSE), F1 Score, $R^{2}$ and Training Time. In line with these results, the highest score was obtained in the $\mathrm{R}^{2}$ comparison metric (97%) in the Neural Network (NN). Compared to the others, the results of Neural Network (NN) were more successful, but the Training Time (245 sec) in the Neural Network (NN) method is by far more than the other ML methods, which shows us that the NN method requires a very high computing process. As a result of the comparison, another outstanding Ensemble-based ML method is Decision Tree. This is because besides the very low Training Time $(5\sec)$, it has managed to be the 2nd ML algorithm with the highest $\mathrm{R}^{2}$ score (96%). Apart from these, among other ML methods, SVM performed slightly less well $(\mathrm{R}^{2}$ 91%) in solving this complex problem. The advanced Gradient Method (95%) and XGBoost (96%), which also have the Ensemble structure, showed a head-to-head performance regarding $\mathrm{R}^{2}$ scores. However, XGBoost (30 sec) has a very short Training Time compared to Gradient Boosting (180 sec). As a result, the approach of each ML method to solving the complex problem differed from each other, and the success rates and Training Time also differed equally. The most important work to be done here is to choose which ML method you want to achieve according to the limited system in hand and the performance-accuracy dilemma. © 2023 IEEE.
Computation of Reduced Diagnosers for the Fault Diagnosis of Discrete Event Systems
(2014) Kart, Bora Eser; Schmidt, Klaus
Many complex systems in different areas such as manufacturing, telecommunications or transportation can be modeled as discrete event systems (DES). In this paper, we consider the fault diagnosis for DES which is concerned with detecting fault occurrences in a DES within a bounded number of event occurrences by a diagnoser automaton. Hereby, such diagnoser is able to observe a subset of the system events and the maximum required number of event occurrences until a fault detection is denoted as the worst case detection delay (WCDD). The main contribution of the paper is an approach for reducing the number of required observations for fault diagnosis without increasing the WCDD. As a result, it is possible to determine a diagnoser with a small size which is essential in practical applications. We first develop an algorithm for computing the WCDD and then adapt an approach for the reduction of the observable event set in order to obtain a reduced diagnoser. The application of our method to a communication system example demonstrates its practicability.
Citation - Scopus: 2
Computation of Supervisors for Fault-Recovery and Repair for Discrete Event Systems
(Univelt Inc., 2014) Sülek, A.N.; Schmidt, K.W.; 17337; 107424
In this paper, we study the fault-recovery and repair of discrete event systems (DES). To this end, we first develop a new method for the fault-recovery of DES. In particular, we compute a fault-recovery supervisor that follows the specified nominal system behavior until a fault-occurrence, that continues its operation according to a degraded specification after a fault and that finally converges to a desired behavior after fault. We next show that our method is also applicable to system repair and we propose an iterative procedure that determines a supervisor for an arbitrary number of fault occurrences and system repairs. We demonstrate our method with a manufacturing system example. © IFAC.
Citation - WoS: 9
Citation - Scopus: 10
Computation of Supervisors for Reconfigurable Machine Tools
(Springer, 2015) Schmidt, Klaus Werner; 17337
The rapid reconfiguration of manufacturing systems is an important issue in today's manufacturing technology in order to adjust the production to varying product demands and types. In this paper, we study the control of reconfigurable machine tools (RMTs) with the aim of fast reconfiguration and an easy controller implementation. We first formulate a particular reconfiguration problem for RMTs in a discrete event system setting, and then provide a necessary and sufficient condition for its solution. Moreover, we propose a polynomial-time algorithm for the construction of a reconfiguration supervisor as the composition of one modular supervisor for each separate RMT configuration. Each modular supervisor operates in three modes. In the first mode, it tracks the plant state if its corresponding configuration is inactive. In the second mode, it performs a configuration change if its corresponding configuration becomes active and in the third mode, it follows the specified behavior of its corresponding configuration if the configuration is active. An important property of the proposed reconfiguration supervisor is that it performs reconfigurations in a bounded number of event occurrences. In addition, the modular realization of our reconfiguration supervisor enables controller modifications such as adding or removing configurations during run-time. All results presented in the paper are illustrated by an RMT example.
Citation - WoS: 2
Citation - Scopus: 6
Controller Area Network With Priority Queues and Fifo Queues: Improved Schedulability Analysis and Message Set Extension
(inderscience Enterprises Ltd, 2016) Schmidt, Klaus Werner; Alkan, Burak; Schmidt, Ece Guran; Karani, Duygu Culum; Karakaya, Utku; 17337
Controller area network (CAN) enables communication of electronic control units (ECUs) via messages using priority-based arbitration, which requires the implementation of priority queues (PQs) in the ECU device driver. Nevertheless, it is possible that not all ECUs on a CAN support PQs but use FIFO queues (FQs) instead. In this case, the classical CAN scheduling model with PQs is not suitable for the computation of message worst-case responsetimes (WCRTs) that are essential for verifying the correct vehicle operation. This paper considers an existing scheduling model for CAN with both PQs and FQs. First, an improved algorithm for speeding up the WCRT computation is proposed. Second, the practical case where an existing CAN message set is extended by new messages is addressed. An original algorithm for assigning priorities to new messages while keeping the priority order of existing messages is developed. Both algorithms are evaluated by computational experiments.
Controller Design for Cacc With Time-Varying Communication Delays
(Ieee, 2023) Soysal, Gokhan; Schmidt, Klaus Werner; Bingol, Hilal; 218795
Cooperative Adaptive Cruise Control (CACC) aims at the safe and comfortable travel of vehicles at short distances in the form of platoons. Hereby, it is generally desired to attenuate disturbances along vehicles in a platoon, which is captured by different string stability conditions. In this paper, we focus on L-infinity string stability. This condition ensures reducing the magnitude of the acceleration signal along the platoon, which helps to avoid actuator saturation and increases driving comfort. Since the performance of CACC is adversely affected by time-varying communication and actuator delays, we develop the first controller design method for L-infinity-string stability, combining the Lyapunov-Krasovskii method and our custom bisection algorithm. Simulation experiments demonstrate the effectiveness of our method.
Citation - Scopus: 3
Controller Design for Quadrotor-Slung Load System With Swing Angle Constraints Using Particle Swarm Optimization
(Institute of Electrical and Electronics Engineers Inc., 2021) Cosan, O.; Degirmenci, B.; Ergezer, H.; Ozgehan, M.; Ates, A.; 293396
In this paper, the controller is designed for a quadrotor carrying a slung load with a rope. When we consider the quadrotor and load pair, there are two cases: the quadrotor carries the load, and the load is on the ground. Since the dynamics of the system are different for these two cases, they must be considered separately. Therefore, a different PID controller is designed for each case. The necessary mechanism has been created to ensure that the transitions between these two controllers are smooth. The controller coefficients are adjusted so that the swing angles of the load are minimal. IMU has been added to the load-bearing mechanism to find out what angle the load is. Also, images of the load have been obtained with the camera located under the quadrotor. The swing angles have been calculated according to the position of the load in the image. Although our physical system studies continue, both the IMU and camera models have been created and integrated into the quadrotor-slung load model. PID coefficients have been obtained using the Particle Swarm Optimization method. Tests have been carried out on different flight profiles and the results obtained are presented. © 2021 IEEE.
Citation - WoS: 6
Citation - Scopus: 6
Design and Implementation of an Electrode Feed Rate Control System in the Electrochemical Drilling Process
(Springer Heidelberg, 2022) Cogun, Can; Ozerkan, Haci Bekir; 3837
The interelectrode gap distance control is essential for preventing short circuit and spark discharge occurrences in the machining gap and ensuring a constant distance between the tool electrode (shortly electrode) and the workpiece throughout the electrochemical drilling (ECD) process. In this study, a gap distance control system was designed and implemented in the constructed ECD machine tool. The gap distance control strategy was based on the machining current's discrete measurement (in microsecond intervals) and changing the gap distance according to a set current value by feeding the electrode towards the workpiece or retracting it during the ECD process. The small diameter deep hole ECD experiments were conducted using 0.5 mm diameter side insulated tubular rotational electrodes with through-hole electrolyte flushing to drill Hadfield and AISI 1040 steels. The experimental results demonstrated the success of the developed control system in ECD operations yielding uniform hole geometries and smooth hole surfaces. The use of the control system eliminated the undesirable formations of spark discharges and short circuit pulses.
Design and Implementation of Visual Simultaneous Localization and Mapping (Vslam) Navigation System
(Ieee, 2021) Ergezer, Halit; Bekcan, Arda; 293396
It is very important to guess the location of the redetected objects and loop closures with the visual simultaneous localization and mapping system (VSLAM), one of the biggest problems of a mobile robot. VSLAM makes it possible to eliminate and/or reduce these applications' errors and realize or improve the robot's direction and position correctly by creating a map of the environment. This study aims to achieve an autonomous indoor/outdoor navigation of a ground robot using VSLAM algorithm in an unknown environment using a monocular camera. In this context, the theoretical information was tested in real-world conditions. Performance of localization and loop closing were compared based on the results obtained by experiments
Citation - Scopus: 2
Determination of Onset of Yield Due To Material Properties in a Heat Generating Two-Layered Compound Cylinder
(2013) Gulgec, M.; Ozturk, A.; 4168
In this theoretical study, based on Tresca's yield criterion and its associated flow rule, the elastic deformation of a centrally heated compound cylinder with fixed ends is investigated analytically by taking into consideration not only the geometrical but also the material parameters such as yield strength, modulus of elasticity, Poisson's ratio, thermal conductivity and coefficient of thermal expansion. These material parameters are assumed to be independent of the temperature. The compound cylinder is assumed to be very long such that axisymmetric condition exists. Both of the constituent materials of the two layers are supposed to be elastic-perfectly plastic materials. There is heat generation in the interior solid cylinder but no heat generation in the outer hollow cylinder. Both of the cylinders are assumed to be bounded perfectly at the interface. Elastic stress analysis is performed to prevent yield in the compound cylinder. © (2013) Trans Tech Publications, Switzerland.
Citation - WoS: 15
Citation - Scopus: 15
Developing and Implementation of an Optimization Technique for Solar Chimney Power Plant With Machine Learning
(Asme, 2021) Kocak, Eyup; Bayer, Ozgur; Beldek, Ulas; Yapic, Ekin Ozgirgin; Ayli, Ece; Ulucak, Oguzhan; 59950; 31329; 265836
Green energy has seen a huge surge of interest recently due to various environmental and financial reasons. To extract the most out of a renewable system and to go greener, new approaches are evolving. In this paper, the capability of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System in geometrical optimization of a solar chimney power plant (SCPP) to enhance generated power is investigated to reduce the time cost and errors when optimization is performed with numerical or experimental methods. It is seen that both properly constructed artificial neural networks (ANN) and adaptive-network-based fuzzy inference system (ANFIS) optimized geometries give higher performance than the numerical results. Also, to validate the accuracy of the ANN and ANFIS predictions, the obtained results are compared with the numerical results. Both soft computing methods over predict the power output values with MRE values of 12.36% and 7.25% for ANN and ANFIS, respectively. It is seen that by utilizing ANN and ANFIS algorithms, more power can be extracted from the SCPP system compared to conventional computational fluid dynamics (CFD) optimized geometry with trying a lot more geometries in a notably less time when it is compared with the numerical technique. It is worth mentioning that the optimization method that is developed can be implemented to all engineering problems that need geometric optimization to maximize or minimize the objective function.
Citation - WoS: 15
Citation - Scopus: 17
Distributed Real-Time Protocols for Industrial Control Systems: Framework and Examples
(Ieee Computer Soc, 2012) Schmidt, Klaus Werner; Schmidt, Ece Guran; 17337
The automation of today's large-scale industrial systems relies on the operation of distributed controller devices that perform local computations and exchange information via communication networks. The subject of this paper is the development of a family of shared-medium industrial communication protocols that support the transmission of real-time (RT) and nonreal-time (nRT) data among distributed controller devices. Different from existing protocols, we suggest to incorporate information that is available from the control application in the protocol definition. As a result, our protocols dynamically change the bandwidth allocation on the shared medium according to the instantaneous communication requirements while ensuring hard RT guarantees. Following the recent developments in industrial automation, our protocols can be realized as software layers on top of low-cost conventional Ethernet.
Citation - WoS: 7
Citation - Scopus: 6
Dynamic Flat-Topped Laser Beam Shaping Method Using Mixed Region Amplitude Freedom Algorithm
(Springer Heidelberg, 2022) Arpali, Caglar; Arpali, Serap Altay; Altemimi, Mohammed Fawzi; Alsaka, Dina Yaqoob; 20809
A dynamic beam shaping method is proposed for the generation of flat-top beams (FTBs) in the far field. Using the mixed-region amplitude freedom algorithm, this new method is used to design the required phase distribution encoded on a spatial light modulator for the generation of FTB profiles. The characteristics of these new beam shaping methods are used as beam parameters, such as the laser beam size, the beam intensity of square FTBs, and the root-mean-square error (RMSE). Using our proposed method, the theoretical performance of beam intensity shaping is improved to an RMSE < 0.02 with a minimum number of iterations of phase reconstruction. Using the phase hologram of dynamic beam shaping, theoretical and experimental comparisons of edge steepness and plateau uniformity were established for the square FTBs of variable beam sizes. It is shown that the dynamic beam shaping of FTBs can produce high intensity uniformity in the plateau region with steep edges, which makes it an effective tool, especially for laser machining applications.

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