Research on transfer alignment for increased speed and accuracy

Kayasal, Uğur
In this thesis, rapid transfer alignment algorithm for a helicopter launched guided munition is studied. Transfer alignment is the process of initialization of a guided munition’s inertial navigation system with the aid of the carrier platform’s navigation system, which is generally done by comparing the navigation data of missile and carrier’s navigation data. In the literature, there are different studies of transfer alignment, especially for aircraft launched munitions. One important problem in transfer alignment is the attitude uncertainty of lever arm between munition’s and carrier’s navigation systems. In order to overcome this problem, most of the studies in the literature do not use carrier’s attitude data in the transfer alignment, only velocity data is used. In order to estimate attitude and related inertial sensor errors, specific maneuvers of carrier platform are required which can take 1-5 minutes. The purpose of this thesis is to compensate the errors arising from the dynamics of the Helicopter, lever arm, mechanical vibration effects and inertial sensor error amplification, thus designing a transfer alignment algorithm under real environment conditions. The algorithm design begins with observability analysis, which is not done for helicopter transfer alignment in literature. In order to make proper compensations, characterization and modeling of vibration and lever arm environment is done for the helicopter. Also, vibration based errors of MEMS based inertial sensors are experimentally shown. The developed transfer alignment algorithm is tested by simulated and experimental data.


Development of artificial neural network based design tool for aircraft engine bolted flange connection subject to combined axial and moment load
Sanlı, Tahir Volkan; Kayran, Altan; Department of Aerospace Engineering (2018)
In this thesis, a design tool using artificial neural network (ANN) is developed for the bolted flange connections, which enables the user to analyze typical aircraft engine connections subjected to combined axial and bending moment in a fast yet very accurate way. The neural network trained for the design tool uses the database generated by numerous finite element analyses for different combinations of parametric design variables of the bolted flange connection. The defined parameters are the number of bol...
Control and guidance of an unmanned sea surface vehicle
Ahıska, Kenan; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2012)
In this thesis, control and guidance algorithms for unmanned sea surface vehicles are studied. To design control algorithms of different complexity, first a mathematical model for an unmanned sea surface vehicle is derived. The dynamical and kinematical equations for a sea surface vehicle are obtained, and they are adapted to real life conditions with necessary additions and simplifications. The forces and torques effecting on the vehicle are investigated in detail. Control algorithms for under-actuated six...
Yildirim, Alper; Kayran, Altan; Gulasik, Hasan; Çöker, Demirkan; Gürses, Ercan (2015-11-19)
In bolted flange connections, commonly utilized in aircraft engine designs, structural integrity and minimization of the weight are achieved by the optimum combination of the design parameters utilizing the outcome of Many structural analyses. Bolt size, the number of bolts, bolt locations, casing thickness, flange thickness, bolt preload, and axial external force are some of the critical design parameters in bolted flange connections. Theoretical analysis and finite element analysis (FEA) are two main appr...
Use of artificial neural network in rotorcraft cooling system
Akin, Altug; Kahveci, Harika Senem (2019-07-01)
In this study, an Artificial Neural Network (ANN) is used to determine the surface temperatures of the avionics equipment located in an avionics bay of a rotorcraft. The bay is cooled via a system of a fan that supplies ambient air to the interior of the bay and an exhaust. A Feedforward Multi-Layer ANN is used with the input parameters of the fan and exhaust locations and the air mass flow rate of the fan. For training of the network, the results obtained by a large number of Computational Fluid Dynamics (...
Prediction of Nonlinear Drift Demands for Buildings with Recurrent Neural Networks
Kocamaz, Korhan; Binici, Barış; Tuncay, Kağan (2021-09-08)
Application of deep learning algorithms to the problems of structural engineering is an emerging research field. Inthis study, a deep learning algorithm, namely recurrent neural network (RNN), is applied to tackle a problemrelated to the assessment of reinforced concrete buildings. Inter-storey drift ratio profile of a structure is a quiteimportant parameter while conducting assessment procedures. In general, procedures require a series of timeconsuming nonlinear dynamic analysis. In this study, an extensiv...
Citation Formats
U. Kayasal, “Research on transfer alignment for increased speed and accuracy,” Ph.D. - Doctoral Program, Middle East Technical University, 2012.