Abstract: As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.
Abstract: In this paper, it is aimed to improve autonomous flight
performance of a load-carrying (payload: 3 kg and total: 6kg)
unmanned aerial vehicle (UAV) through active wing and horizontal
tail active morphing and also integrated autopilot system parameters
(i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing
and horizontal tail during flight) design. For this purpose, a loadcarrying
UAV (i.e. ZANKA-II) is manufactured in Erciyes
University, College of Aviation, Model Aircraft Laboratory is
benefited. Optimum values of UAV parameters and autopilot
parameters are obtained using a stochastic optimization method.
Using this approach autonomous flight performance of UAV is
substantially improved and also in some adverse weather conditions
an opportunity for safe flight is satisfied. Active morphing and
integrated design approach gives confidence, high performance and
easy-utility request of UAV users.
Abstract: In this paper, an autonomous hovering control method
of multicopter using only Web camera is proposed. Recently, various
control method of an autonomous flight for multicopter are proposed.
But, in the previous proposed methods, a motion capture system
(i. e., OptiTrack) and laser range finder are often used to measure
the position and posture of multicopter. To achieve an autonomous
flight control of multicopter with simple equipments, we propose
an autonomous flight control method using AR marker and Web
camera. AR marker can measure the position of multicopter with
Cartesian coordinate in three dimensional, then its position connects
with aileron, elevator, and accelerator throttle operation. A simple
PID control method is applied to the each operation and adjust
the controller gains. Experimental results are given to show the
effectiveness of our proposed method. Moreover, another simple
operation method for autonomous flight control multicopter is also
proposed.
Abstract: This paper describes the design process and the realtime validation of an innovative autonomous mid-air flight and landing system developed by the Italian Aerospace Research Center in the framework of the Italian national funded project TECVOL (Technologies for the Autonomous Flight). In the paper it is provided an insight of the whole development process of the system under study. In particular, the project framework is illustrated at first, then the functional context and the adopted design and testing approach are described, and finally the on-ground validation test rig on purpose designed is addressed in details. Furthermore, the hardwarein- the-loop validation of the autonomous mid-air flight and landing system by means of the real-time test rig is described and discussed.
Abstract: In the present era of aviation technology, autonomous navigation and control have emerged as a prime area of active research. Owing to the tremendous developments in the field, autonomous controls have led today’s engineers to claim that future of aerospace vehicle is unmanned. Development of guidance and navigation algorithms for an unmanned aerial vehicle (UAV) is an extremely challenging task, which requires efforts to meet strict, and at times, conflicting goals of guidance and control. In this paper, aircraft altitude and heading controllers and an efficient algorithm for self-governing navigation using MATLAB® mapping toolbox is presented which also enables loitering of a fixed wing UAV over a specified area. For this purpose, a nonlinear mathematical model of a UAV is used. The nonlinear model is linearized around a stable trim point and decoupled for controller design. The linear controllers are tested on the nonlinear aircraft model and navigation algorithm is subsequently developed for for autonomous flight of the UAV. The results are presented for trajectory controllers and waypoint based navigation. Our investigation reveals that MATLAB® mapping toolbox can be exploited to successfully deliver an efficient algorithm for autonomous aerial navigation for a UAV.