Altan, Aytaç | Bayraktar, Köksal | Hacıoğlu, Rıfat
Proceedings | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.1433 - 1436
In this stuidy, the position information from ultrasound sensors on UAV related to floor gallery mine passed through the filter, it is aimed to control the position of simultaneously creating the optimum environmental map. The simultaneous in galleries made mapping, mine the data of air to the designated central monitoring system with real-time location information is transmitted to the ventilation system, which is intended to more effectively work in the mines. The gallery maps which simultaneous location and mapping information obtained by UAV Extended Kalman Filter algorithms processed were obtained experimentally. © 2016 IEEE.
Karasu, Seçkin | Altan, Aytaç | Saraç, Zehra | Hacıoğlu, Rıfat
Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1433 - 1436
In this study, the wind speed prediction model is created that gives a minimum error for different hidden layer neuron numbers and delay step numbers. Using the one-minute time series, the prediction of the next wind speed is performed with the NAR neural network model. The predicted values of wind speed obtained are compared with predicted values of wind speed obtained with filter methods. For different window functions and lengths, wind speed prediction is made using filters with different weight coefficients. For the number of hidden layer neurons is 14 and the number of delay steps is 10, MAE, MSE and RMSE values are calculated . . .as 0.0315, 0.0019, 0.0445, respectively, with NAR neural network. It is seen that the proposed method for the wind speed dataset has a higher prediction performance than thefilter methods. © 2017 IEEE Daha fazlası Daha az
Altan, Aytaç | Köksal, Kerem | Hacıoğlu, Rıfat
Article | 2017 | Karaelmas Fen ve Mühendislik Dergisi7 ( 1 ) , pp.218 - 227
Bu çalışmada, görsel çizgi (rota) takibi için İnsansız Hava Aracı (İHA) üzerinde bulunan 3 eksenli yalpanın dış bozucu etki altında model öngörülü denetimi gerçekleştirilmektedir. İHA ile görsel çizgi takibi için Tanjant Vektör Alan Kılavuz (TVAK) yöntemi kullanılmaktadır. Dış ortam ve kapalı ortamda yapılan testlerde, ön tanımlaması yapılan çizginin görüntü işleme algoritmalarıyla tespiti ve sonrasında TVAK yöntemi kullanılarak rota takip işlemi gerçekleştirilmektedir. İHA’nın alçak ve yüksek irtifa uçuşlarında rota takibi başarım oranları deneysel olarak gözlemlenmektedir. Elde edilen sonuçlar PID denetime sahip yalpadan elde edil . . .en veriler ile karşılaştırılmaktadır. Dış bozucu etki altında TVAK yöntemi ile rota takibi için İHA üzerindeki 3 eksenli yalpanın MPC denetiminde PID ile denetime göre başarılı sonuçlar elde edilmektedir. In this study, Model Predictive Control (MPC) is performed under the external disturbance effect of the 3-axis gimbal on the Unmanned Aerial Vehicle (UAV) for visual line tracking. The Tangent Vector Fields Guide (TVFG) method is used for visual line tracking with UAV. In the tests performed in the outdoor and indoor environments, the pre-defined line is detected with the image processing algorithms and then the line tracking process is performed using the TVFG method. The visual line tracking success rates in the low and high altitude of UAV flight are observed experimentally. The obtained results are compared with data obtained by the gimbal having PID control. The successful results are obtained with MPC control according to PID control of 3 axis gimbal on UAV under external disturbance for visual line tracking using TVFG method Daha fazlası Daha az
Kulu, Nükhet | Başkaya, Merve | Keleş, Aysel | Altan, Aytaç | Hacıoğlu, Rıfat
Proceedings | 2018 | 2018 2ND INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES (ISMSIT) , pp.290 - 293
In this study, it is aimed to determine the number of reference fruits and health status (sturdy, rotten, mottled, non-spotted) by using real-time image or recorded video taken from the autonomous Unmanned Aerial Vehicle (UAV) camera in orchards. In the determinations made by using image processing techniques, sturdy-rotten and mottled-speckless distinction are made for oranges and apricots, respectively. These distinction and determination processes are carried out using highly trained classifiers. Three types of multi-trained classifiers performance have been compared and a highly trained classifier which has high performance has . . .been preferred for object detection. The accuracy of the Haar, local binary pattern (LBP), and histogram of oriented gradients (HOG) classifiers are compared in Python using the open source computer vision library. It has been shown experimentally that Haar classifier achieves high performance in determining real-time reference fruit health status and yield. Daha fazlası Daha az
Altan, Aytaç | Hacıoğlu, Rıfat
Article | 2018 | JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI21 ( 3 ) , pp.559 - 564
The 3D printers widely used in the world are produced in different mechanical and electronic designs. The 3D printers which have various mechanical structures such as cartesian, delta and core (xy, xz) already are used open source code software such as Sprinter, Marlin, Cura 3D and Teacup. The control of the 3D printers is usually done by the classical Propotional-Integral-Derivative (PID) control algorithm. In this study, we have developed for the designed 3D printer a new software by using adaptive PID control algorithm instead of classical PID. Five step motors of the designed 3D printer are controlled by the adaptive PID. In add . . .ition, there are both heating and cooling processes in the extruder system and these processes are controlled by the adaptive PID. The mechanical design uses a belt and pulley drive system which is suitable for accelerated movements. In the system software, 3D Printing Software Pipeline (input model, orientation and positioning, support structures, slicing, path planning, machine instructions) is applied. The control algorithms for extruder and step motors are prepared as separate function files in software implemented in C. It has been observed that the designed software is particularly successful in eliminating errors on the surface of the products Daha fazlası Daha az
Altan, Aytaç | Hacıoğlu, Rıfat
Proceedings | 2014 | 2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) , pp.1686 - 1689
In this study, unmanned vehicles used for target tracking camera RRP (revolute revolute prismatic) joint structure with a three-jointed robot arm with the position, velocity and acceleration control is made. In order to be able to follow the specified trajectory, the system used in the control of the robot arm with joint structure RRP target tracking model based on changing according to the structure proposed by the MPC is implemented. Also the PID (Proportional Integral Dervative) is provided with control comparison was made. MATLAB/Simulink simulations performed unmanned vehicles used for target tracking in robotic camera control . . .with the system were investigated in the MPC Daha fazlası Daha az
Altan, Aytaç | Hacıoğlu, Rıfat
Conference Object | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.1686 - 1689
This study focuses on the modelling of 3 axis gimbal system with the RRR joint structure on the Unmanned Aerial Vehicle (UAV), which is autonomously moving for the target tracking, based on experimental input (motor velocities) and output (end effector position) data. The fact that UAVs move in a certain direction and that the camera on the end effector of the gimbal system on it is adhere to the correct target attracts many researchers. The transfer function of the 3 axis gimbal system is obtained by linearly structured OE-Output Error model using experimentally obtained data under different external disturbance effects. Model degr . . .ee is determined and data set based verification is applied. Also, the performance is compared by examining the effect of external disturbance in the transfer function obtained. © 2017 IEEE Daha fazlası Daha az