2 results listed
Küçük insansız hava araçları(İHA) bir noktaya iniş yapacağı zaman üzerindeki konum sensörlerinin
hassasiyetinin düşük olması, araç gövdesine etki eden rüzgar vs. sebeplerle yatay düzlemde belli bir
hata ile iniş yapmaktadır. Bu çalışmada ileri kinematik analizi yapılan sistem, mini İHA’ların iniş
yaparken yatay düzlemde yaptığı hatayla orantılı şekilde hareket eden ve iniş yapan İHA’nın havada
yakalanmasını sağlayan bir sistemdir. Çalışmada ele alınan sistem 3 boyutlu tasarım programlarında
tasarlanmıştır. Yapılan tasarımda yer alan mafsallar ile sistemin uç noktasının konumunu içeren giriş-
çıkış Çizelgesu Matlab programı yardımıyla oluşturulmuştur. Elde edilen tablo üzerinden İHA iniş
sistemine ait ileri kinematik modelleri yapay sinir ağları temelli yaklaşımlarla oluşturulmuştur ve bu
modellerin başarısı tablo halinde sunulmuştur.
When a small sized unmanned aerial vehicle(UAV) land a point, because of reasons such as low
sensitivity of its position sensors, the wind effects on vehicles body and etc, small UAV makes a
certain error in the horizontal plane. The system which its forward kinematic analysis was obtained in
this study enables the capture of the UAVs while they are moving in the air. The system moves
according to the error made by the mini UAVs in the horizontal plane during landing. The system was
designed in 3D design programs. The input-output table which contains the position of the end point
of the system and the joints angles was created with the help of Matlab program. The forward
kinematic models of the UAV landing system were formed by artificial neural network based
approaches and the success of these models was presented in tabular form.
International Congress on 3D Printing (Additive Manufacturing) Technologies and Digital Industry
3D-PTC2019
Serkan Caşka
Emrah Kuzu
Ali Uysal
Mustafa Aydin
Nowadays, fossil fuels that have risked extinct and
increasing the cost of those fuels are increased using electric
energy and researches on this issue. Devices such as Mobile
phones, portable computers, electric cars, electric aircraft, etc.
are provided electrical demand by batteries. Knowing the state of
batteries during to continuous using is important for the not
tardiness of work. Many studies on this subject are made. In this
study, the filling rate of the battery modeled in MATLAB
environment was estimated with Coulomb Counting Method and
BP Neural Network methods. Performance comparison between
methods was made
1.st International Conference Energy Systems Engineering
ıcese'17
Musa Matlı
Ali Uysal