Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

Vertical take-off and landing (VTOL) is a type of unmanned aerial vehicle (UAV) that is growing rapidly because its ability to take off and land anywhere in tight spaces. One type of VTOL UAV, the tail-sitter, has the best efficiency. However, besides the efficiency offered, some challenges must still be overcome, including the complexity of combining the ability to hover like a helicopter and fly horizontally like a fixed-wing aircraft. This research has two contributions: in the form of how the analytical model is generated and the tools used (specifically for the small VTOL quad tail-sitter UAV) and how to utilize off-the-shelf components for UAV empirical modeling. This research focuses on increasing the speed and accuracy of the UAV VTOL control design in fixed-wing mode. The first step is to carry out analysis and simulation. The model is analytically obtained using OpenVSP in longitudinal and lateral modes. The next step is to realize this analytical model for both the aircraft and the controls. The third step is to measure the flight characteristics of the aircraft. Based on the data recorded during flights, an empirical model is made using system identification technique. The final step is to vali-date the analytical model with the empirical model. The results show that the characteristics of the analytical mode fulfill the specified requirements and are close to the empirical model. Thus, it can be concluded that the analytical model can be implemented directly, and consequently, the VTOL UAV design and development process has been shortened

PID vs LQR controller for tilt rotor airplane

The main thematic of this paper is controlling the main manoeuvers of a tilt rotor UAV airplane in several modes such as vertical takeoff and landing, longitudinal translation and the most important phase which deal with the transition from the helicopter mode to the airplane mode and visversa based on a new actuators combination technique for specially the yaw motion with not referring to rotor speed control strategy which is used in controlling the attitude of a huge number of vehicles nowadays. This new actuator combination is inspired from that the transient response of a trirotor using tilting motion dynamics provides a faster response than using rotor speed dynamics. In the literature, a lot of control technics are used for stabilizing and guarantee the necessary manoeuvers for executing such task, a multiple Attitude and Altitude PID controllers were chosen for a simple linear model of our tilt rotor airplane in order to fulfill the desired trajectory, for reasons of complexity of our model the multiple PID controller doesnt take into consideration all the coupling that exists between the degrees of freedom in our model, so an LQR controller is adopted for more feasible solution of complex manoeuvering, the both controllers need linearization of the model for an easy implementation

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 182, July 1978

This bibliography lists 165 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1978

Aircraft Modeling and Simulation

Various aerodynamics, structural dynamics, and control design and experimental studies are presented with the aim of advancing green and morphing aircraft research. The results obtained with an in-house CFD code are compared and validated with those of two NASA codes. The aerodynamical model of the UAS-S45 morphing wing as well as the structural model of a morphing winglet are presented. A new design methodology for oleo-pneumatic landing gear drop impact dynamics is presented as well as its experimental validation. The design of a nonlinear dynamic inversion (NDI)-based disturbance rejection control on a tailless aircraft is presented, including its validation using wind tunnel tests

UAV Model-based Flight Control with Artificial Neural Networks: A Survey

Model-Based Control (MBC) techniques have dominated flight controller designs for Unmanned Aerial Vehicles (UAVs). Despite their success, MBC-based designs rely heavily on the accuracy of the mathematical model of the real plant and they suffer from the explosion of complexity problem. These two challenges may be mitigated by Artificial Neural Networks (ANNs) that have been widely studied due to their unique features and advantages in system identification and controller design. Viewed from this perspective, this survey provides a comprehensive literature review on combined MBC-ANN techniques that are suitable for UAV flight control, i.e., low-level control. The objective is to pave the way and establish a foundation for efficient controller designs with performance guarantees. A reference template is used throughout the survey as a common basis for comparative studies to fairly determine capabilities and limitations of existing research. The end-result offers supported information for advantages, disadvantages and applicability of a family of relevant controllers to UAV prototypes