A Discrete-Time Nonlinear Robust Controller for Current Regulation in PMSM Drives

Turker, Turker,Yanik, Gurcan,Buyukkeles, Umit,Bakan, Faruk,Mese, Erkan The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1

In this paper, a discrete-time robust current controller is proposed for PMSM drives. The structure of the proposed controller is quite simple and does not require high computational resource. The only difference of the proposed controller from the classical dead-beat controller is the integral term which can easily be implemented in a PMSM drive. The stability analysis of the proposed controller is performed accounting in parametric uncertainties, unmodelled dynamics and disturbances in the mathematical model. The boundedness of the dynamical system and asymptotic convergence of dq-axes currents to their reference values are provided under certain conditions. Various simulation and experimental studies are performed and the results taken at different operation conditions show the validity of the proposed controller.

A Discrete-Time Nonlinear Robust Controller for Current Regulation in PMSM Drives

Turker Turker,Gurcan Yanik,Umit Buyukkeles,Faruk Bakan,Erkan Mese 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.4

In this paper, a discrete-time robust current controller is proposed for PMSM drives. The structure of the proposed controller is quite simple and does not require high computational resource. The only difference of the proposed controller from the classical dead-beat controller is the integral term which can easily be implemented in a PMSM drive. The stability analysis of the proposed controller is performed accounting in parametric uncertainties, unmodelled dynamics and disturbances in the mathematical model. The boundedness of the dynamical system and asymptotic convergence of dq-axes currents to their reference values are provided under certain conditions. Various simulation and experimental studies are performed and the results taken at different operation conditions show the validity of the proposed controller.

Effects of overdenture attachment systems with different working principles on stress transmission: A three-dimensional finite element study

Turker, Nurullah,Buyukkaplan, Ulviye Sebnem The Korean Academy of Prosthodonitics 2020 The Journal of Advanced Prosthodontics Vol.12 No.6

PURPOSE. The aim of the present study was to compare the stress distributions on the dental implants, abutments, and bone caused by different overdenture attachment types under functional chewing forces. MATERIALS AND METHODS. The 3D finite element models of the mandible, dental implants, attachment types, and prostheses were prepared. In accordance with a conventional dental implant supported overdenture design, the dental implants were positioned at the bone level in the canine teeth region bilaterally. A total of eight models using eight different attachment systems were used in this study. All the models were loaded to simulate chewing forces generated during the centric relationship (450 N), lateral movement (400 N), protrusive movement (400 N), and also in the presence of a food mass unilaterally (200 N). Stress outputs were obtained as the maximum principal stress and the equivalent von-Mises stress. RESULTS. In all attachment types, higher stress values were observed in the abutments, dental implants, and bone in the magnet attachments in different loading conditions. The highest stress values were observed among the magnet systems in the components of the Titanmagnetics model in all loading conditions (stresses were 15.4, 17.7, and 33.1 MPa on abutment, dental implant, and bone, respectively). The lowest stress value was observed in the models of Zest and O-Ring attachments. CONCLUSION. The results of the present study implied that attachment types permitting rotation and tolerating various angles created lower stresses on the bone, dental implants, and abutments.

Structural evaluation of Aspendos (Belkis) Masonry Bridge

Turker, Temel Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.50 No.4

In this study, the structural performance of a seven span masonry arch bridge was evaluated. Investigations were performed on Aspendos (Belkis) Masonry Arch Bridge which was located on road of Aspendos Acropolis City in Antalya, Turkey. The old bridge was constructed in the early of fourth century AD, but it was exposed to the earthquakes in this region and the overloading by the river water. The old bridge was severely damaged and collapsed by probably an earthquake many years ago and a new bridge was then reconstructed on the remains of this old bridge by Seljuk in the 13th century. The bridge has also been affected from overflowing especially in the spring of each year, so some protective measures should be taken for this monumental bridge. Therefore, the structural performance under these loading has to be known. For this purpose, an initial finite element model was developed for the bridge and it was calibrated according to ambient vibration test results. After that, it was analyzed for different load cases such as dead, live, earthquake and overflow. Three load combinations were taken into account by deriving from these load cases. The displacements and the stresses for these combination cases were attained and compared with each other. The structural performance of Aspendos Masonry Arch Bridge was determined by considering the demand-capacity ratio for the tensile stress of the mortar used in Aspendos Masonry Arch Bridge. After these investigations, some concluding remarks and offers were presented at the end of this study.

Rotor Position Estimation Strategy Using Artificial Neural Network for a Novel Design Transverse Flux Machine

Turker, Cigdem Gundogan,Kuyumcu, Feriha Erfan The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.5

The E-Core Transverse Flux Machine is a different design of transverse flux machines combined with reluctance principle. Determination of the rotor position is important for the movement of the ETFM by switching the phase currents in synchronism with the inductance regions of the stator windings. It is the first time that rotor position estimation based on Artificial Neural Network (ANN) is purposed to eliminate the position sensor for the ETFM. Simulation and experimental tests are demonstrated for the feasibility of the proposed estimation algorithm for the exercise bike application of the ETFM.

An effective load increment method for multi modal adaptive pushover analysis of buildings

Turker, K.,Irtem, E. Techno-Press 2007 Structural Engineering and Mechanics, An Int'l Jou Vol.25 No.1

In this study, an effective load increment method for multi modal adaptive non-linear static (pushover) analysis (NSA) for building type structures is presented. In the method, lumped plastisicity approach is adopted and geometrical non-linearties (second-order effects) are included. Non-linear yield conditions of column elements and geometrical non-linearity effects between successive plastic sections are linearized. Thus, load increment needed for formation of plastic sections can be determined directly (without applying iteration or step-by-step techniques) by using linearized yield conditions. After formation of each plastic section, the higher mode effects are considered by utilizing the essentials of traditional response spectrum analysis at linearized regions between plastic sections. Changing dynamic properties due to plastification in the system are used on the calculation of modal lateral loads. Thus, the effects of stiffness changes and local mechanism at the system on lateral load distribution are included. By using the proposed method, solution can be obtained effectively for multi-mode whereby the properties change due to plastifications in the system. In the study, a new procedure for determination of modal lateral loads is also proposed. In order to evaluate the proposed method, a 20 story RC frame building is analyzed and compared with Non-linear Dynamic Analysis (NDA) results and FEMA 356 Non-linear Static Analysis (NSA) procedures using fixed loads distributions (first mode, SRSS and uniform distribution) in terms of different parameters. Second-order effects on response quantities and periods are also investigated. When the NDA results are taken as reference, it is seen that proposed method yield generally better results than all FEMA 356 procedures for all investigated response quantities.

The effects of different surface treatments on the shear bond strengths of two dual-cure resin cements to CAD/CAM restorative materials

Turker, Nurullah,Buyukkaplan, Ulviye Sebnem,Basar, Ebru Kaya,Ozarslan, Mehmet Mustafa The Korean Academy of Prosthodonitics 2020 The Journal of Advanced Prosthodontics Vol.12 No.4

PURPOSE. The aim of the present study was to investigate the effects of surface treatments on the bond strengths between polymer-containing restorative materials and two dual-cure resin cements. MATERIALS AND METHODS. In the present study, rectangular samples prepared from Lava Ultimate (LU) and Vita Enamic (VE) blocks were used. The specimen surfaces were treated using CoJet sandblasting, 50 ㎛ Al₂O₃ sandblasting, % 9 HF (hydrofluoric) acid, ER,Cr:YSGG laser treatment, and Z-Prime. Dual-cure resin cements (TheraCem and 3M RelyX U 200) were applied on each specimen's treated surface. A micro-tensile device was used to evaluate shear bond strength. Statistical analysis was performed using the SAS 9.4v3. RESULTS. While the bond strength using TheraCem with LU or VE was not statistically significant (P=.164), the bond strength using U200 with VE was statistically significant (P=.006). In the TheraCem applied VE groups, Z-Prime and HF acid were statistically different from CoJet, Laser, and Sandblast groups. In comparison of TheraCem used LU group, there was a statistically significant difference between HF acid and other surface treatments. CONCLUSION. The bonding performance between the restorative materials and cements were material type-dependent and surface treatment had a large effect on the bond strength. Within the limitations of the study, the use of both U200 and TheraCem may be suggested if Z-prime was applied to intaglio surfaces of VE. The cementation of LU using TheraCem is suitable after HF acid conditioning of the restoration surfaces.

Neural Network Based Response Prediction of rTMS in Major Depressive Disorder Using QEEG Cordance

Turker Tekin Erguzel,Serhat Ozekes,Selahattin Gultekin,Nevzat Tarhan,Gokben Hizli Sayar,Ali Bayram 대한신경정신의학회 2015 PSYCHIATRY INVESTIGATION Vol.12 No.1

ObjectiveaaThe combination of repetitive transcranial magnetic stimulation (rTMS), a non-pharmacological form of therapy for treating major depressive disorder (MDD), and electroencephalogram (EEG) is a valuable tool for investigating the functional connectivity in the brain. This study aims to explore whether pre-treating frontal quantitative EEG (QEEG) cordance is associated with response to rTMS treatment among MDD patients by using an artificial intelligence approach, artificial neural network (ANN). MethodsaaThe artificial neural network using pre-treatment cordance of frontal QEEG classification was carried out to identify responder or non-responder to rTMS treatment among 55 MDD subjects. The classification performance was evaluated using k-fold cross-validation. ResultsaaThe ANN classification identified responders to rTMS treatment with a sensitivity of 93.33%, and its overall accuracy reached to 89.09%. Area under Receiver Operating Characteristic (ROC) curve (AUC) value for responder detection using 6, 8 and 10 fold cross validation were 0.917, 0.823 and 0.894 respectively. ConclusionaaPotential utility of ANN approach method can be used as a clinical tool in administering rTMS therapy to a targeted group of subjects suffering from MDD. This methodology is more potentially useful to the clinician as prediction is possible using EEG data collected before this treatment process is initiated. It is worth using feature selection algorithms to raise the sensitivity and accuracy values.

Influence of a glide path on the dentinal crack formation of ProTaper Next system

Turker, Sevinc Aktemur,Uzunoglu, Emel The Korean Academy of Conservative Dentistry 2015 Restorative Dentistry & Endodontics Vol.40 No.4

Objectives: The aim was to evaluate dentinal crack formation after root canal preparation with ProTaper Next system (PTN) with and without a glide path. Materials and Methods: Forty-five mesial roots of mandibular first molars were selected. Fifteen teeth were left unprepared and served as controls. The experimental groups consist of mesiobuccal and mesiolingual root canals of remaining 30 teeth, which were divided into 2 groups (n = 15): Group PG/PTN, glide path was created with ProGlider (PG) and then canals were shaped with PTN system; Group PTN, glide path was not prepared and canals were shaped with PTN system only. All roots were sectioned perpendicular to the long axis at 1, 2, 3, 4, 6, and 8 mm from the apex, and the sections were observed under a stereomicroscope. The presence/absence of cracks was recorded. Data were analyzed with chi-square tests with Yates correction. Results: There were no significant differences in crack formation between the PTN with and without glide path preparation. The incidence of cracks observed in PG/PTN and PTN groups was 17.8% and 28.9%, respectively. Conclusions: The creation of a glide path with ProGlider before ProTaper Next rotary system did not influence dentinal crack formation in root canals.

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

Turker Tekin Erguzel,Serhat Ozekes,Selahattin Gultekin,Nevzat Tarhan 대한신경정신의학회 2014 PSYCHIATRY INVESTIGATION Vol.11 No.3

Objective-Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new approach for feature subset selection. Methods-Feature selection process using ant colony optimization (ACO) for 6 channel pre-treatment electroencephalogram (EEG) data from theta and delta frequency bands is combined with back propagation neural network (BPNN) classification method for 147 major depressive disorder (MDD) subjects. Results-BPNN classified R subjects with 91.83% overall accuracy and 95.55% subjects detection sensitivity. Area under ROC curve (AUC) value after feature selection increased from 0.8531 to 0.911. The features selected by the optimization algorithm were Fp1, Fp2, F7, F8, F3 for theta frequency band and eliminated 7 features from 12 to 5 feature subset. Conclusion-ACO feature selection algorithm improves the classification accuracy of BPNN. Using other feature selection algorithms or classifiers to compare the performance for each approach is important to underline the validity and versatility of the designed combination.