Unmanned Aerial Vehicle In Presence Research Articles

Probability of Trajectory Deviation of Unmanned Aerial Vehicle in Presence of Wind

Incorporating unmanned aerial vehicles (UAVs) into the United States National Airspace System would demand enhanced airspace safety technologies for the safety of the UAVs, people, and property on the ground. One of the safety-critical factors to consider is the risk of a UAV deviating from its planned trajectory, which may result in loss of separation between other vehicles or obstacles or may cause early depletion of battery power. In this paper, we studied the effect of wind on UAV trajectory deviation by incorporating wind velocity as a drag component in a six-degrees-of-freedom trajectory simulation comprising a rotorcraft lumped-mass model. Both steady-state wind and wind turbulence effects were investigated. We validated our approach using real flight data from UAV experiments conducted at NASA Langley Research Center. The proposed approach would enable risk-informed decision making by timely mitigation of current and future collision events in an uncertain and dynamic environment.

Super-Twisting Extended State Observer and Sliding Mode Controller for Quadrotor UAV Attitude System in Presence of Wind Gust and Actuator Faults

This article addresses the problem of high precision attitude control for quadrotor unmanned aerial vehicle in presence of wind gust and actuator faults. We consider the effect of those factors as lumped disturbances, and in order to realize the quickly and accurately estimation of the disturbances, we propose a control strategy based on the online disturbance uncertainty estimation and attenuation method. Firstly, an enhanced extended state observer (ESO) is constructed based on the super-twisting (ST) algorithm to estimate and attenuate the impact of wind gust and actuator faults in finite time. And the convergence analysis and parameter selection rule of STESO are given following. Secondly, in order to guarantee the asymptotic convergence of desired attitude timely, a sliding mode control law is derived based on the super-twisting algorithm. And a comprehensive stability analysis for the entire system is presented based on the Lyapunov stability theory. Finally, to demonstrate the efficiency of the proposed solution, numerical simulations and real time experiments are carried out in presences of wind disturbance and actuator faults.

Adaptive Control with Neural Networks-based Disturbance Observer for a Spherical UAV

This paper develops a control scheme for a Spherical Unmanned Aerial Vehicle (UAV) which can be used in complex scenarios where traditional navigation and communications systems would not succeed. The proposed scheme is based on the nonlinear control theory combined with Adaptive Neural-Networks Disturbance Observer (NN-DOB) and controls the attitude and altitude of the UAV in presence of model uncertainties and external disturbances. The NN-DOB can effectively estimate the uncertainties without the knowledge of their bounds and the control system stability is proven using Lyapunov’s stability theorems. Numerical simulation results demonstrate the validity of the proposed method on the UAV under model uncertainties and external disturbances.

Flight formation of UAVs in presence of moving obstacles using fast-dynamic mixed integer linear programming

This paper proposes the implementation of fast-dynamic Mixed Integer Linear Programming (MILP) and Path Smoother for efficient path planning of Unmanned Aerial Vehicles (UAVs) in various flight formations. The UAVs taking part in a cooperative flight are assumed to be equipped with Automatic Dependent Surveillance Broadcast (ADS-B) which enables sharing the flight information with neighboring aircraft. The design and implementation of flights for various formations have been carried out in a generic manner such that multiple UAVs with arbitrarily geographically located base stations can take part in collision-free formation flight. The paper formulates the problem of path of planning in the framework of a novel fast-dynamic MILP and proposes a cost function that minimizes time and energy consumption. The paper presents elaborate construction of constraint equations to enforce the formation to visit pre-defined way-points and avoid the collisions with any intruder aircraft. The performance of the proposed algorithm has been verified and compared with respect to the standard MILP method via a number of simulations carried out using different scenarios featuring multiple UAVs flying in various formations.

Nonlinear control of fixed-wing UAVs in presence of stochastic winds

This paper studies the control of fixed-wing unmanned aerial vehicles (UAVs) in the presence of stochastic winds. A nonlinear controller is designed based on a full nonlinear mathematical model that includes the stochastic wind effects. The air velocity is controlled exclusively using the position of the throttle, and the rest of the dynamics are controlled with the aileron, elevator, and rudder deflections. The nonlinear control design is based on a smooth approximation of a sliding mode controller. An extended Kalman filter (EKF) is proposed for the state estimation and filtering. A case study is presented: landing control of a UAV on a ship deck in the presence of wind based exclusively on LADAR measurements. The effectiveness of the nonlinear control algorithm is illustrated through a simulation example.