Fixed-wing Unmanned Air Vehicles Research Articles

Implementation of the Rauch-Tung-Striebel Smoother for Sensor Compatibility Correction of a Fixed-Wing Unmanned Air Vehicle

This paper presents a complete procedure for sensor compatibility correction of a fixed-wing Unmanned Air Vehicle (UAV). The sensors consist of a differential air pressure transducer for airspeed measurement, two airdata vanes installed on an airdata probe for angle of attack (AoA) and angle of sideslip (AoS) measurement, and an Attitude and Heading Reference System (AHRS) that provides attitude angles, angular rates, and acceleration. The procedure is mainly based on a two pass algorithm called the Rauch-Tung-Striebel (RTS) smoother, which consists of a forward pass Extended Kalman Filter (EKF) and a backward recursion smoother. On top of that, this paper proposes the implementation of the Wiener Type Filter prior to the RTS in order to avoid the complicated process noise covariance matrix estimation. Furthermore, an easy to implement airdata measurement noise variance estimation method is introduced. The method estimates the airdata and subsequently the noise variances using the ground speed and ascent rate provided by the Global Positioning System (GPS). It incorporates the idea of data regionality by assuming that some sort of statistical relation exists between nearby data points. Root mean square deviation (RMSD) is being employed to justify the sensor compatibility. The result shows that the presented procedure is easy to implement and it improves the UAV sensor data compatibility significantly.

A linear-quadratic-Gaussian approach for automatic flight control of fixed-wing unmanned air vehicles

AbstractThis paper presents the design and implementation of automatic flight controllers for a fixed-wing unmanned air vehicle (UAV) by using a linear-quadratic-Gaussian (LQG) control approach. The LQG design is able to retain the guaranteed closed-loop stability of the linear-quadratic regulator (LQR) while having incomplete state measurement. Instead of feeding back the actual states to form the control law, the estimated states provided by a separately designed optimal observer, i.e. the Kalman filter are used. The automatic flight controllers that include outer-loop controls are constructed based on two independent LQG regulators which govern the longitudinal and lateral dynamics of the UAV respectively. The resulting controllers are structurally simple and thus efficient enough to be easily realized with limited onboard computing resource. In this paper, the design of the LQG controllers is described while the navigation and guidance algorithm based on Global Positioning System (GPS) data is also outlined. In order to validate the performance of the automatic flight control system, a series of flight tests have been conducted. Significant results are presented and discussed in detail. Overall, the flight-test results show that it is highly feasible and effective to apply the computationally efficient LQG controllers on a fixed-wing UAV system with a relatively simple onboard system. On the other hand, a fully automatic 44km cross-sea flight demonstration was successfully conducted using the LQG-based flight controllers. Detailed description regarding the event and some significant flight data are given.

Transition Control for a fixed-wing Vertical Take-Off and Landing Aircraft

AbstractThis paper addresses the problem of autonomous transition between hover and level flight for a model-scale fixed-wing Unmanned Air Vehicle (UAV). The UAV flight envelope is divided into hover, transition and level flight. Each flight region employs different controllers and the overall system is robust provided that there exists appropriate switching logic. Classic linear optimal control techniques provide stabilization in hover and level flight as well as reference tracking during the transition between these two distinct regions of the flight envelope. The reference trajectories are generated with some physical insight about the system, using very few parameters. Simulation results demonstrate the performance and robustness of the proposed solution, namely under the effect of sensor noise.

Design and implementation of linear-quadratic-Gaussian stability augmentation autopilot for unmanned air vehicle

AbstractThe linear-quadratic-Gaussian (LQG) control synthesis has the advantage of dealing with the uncertain linear systems disturbed by additive white Gaussian noise while having incomplete system state information available for control-loop feedback. This paper hence explores the feasibility of designing and implementing a stability augmentation autopilot for fixed-wing unmanned air vehicles using the LQG approach. The autopilot is composed of two independently designed LQG controllers which control the longitudinal and lateral motions of the aircraft respectively. The corresponding linear models are obtained through a system identification routine which makes use of the combination of two well-established identification methods, namely the subspace method and prediction error method. The two identification methods complement each other well and this paper shows that the proposed system identification scheme is capable of attaining satisfactory state-space models. A complete autopilot design procedure is devised and it is shown that the design process is simple and effective. Resulting longitudinal and lateral controllers are successfully verified in computer simulations and actual flight tests. The flight test results are presented in the paper and they are found to be consistent with the simulation results.

Experimental validation of an autonomous control system on a mobile robot platform

An autonomous control system designed for a non-holonomic wheeled mobile robot that is programmed to emulate a fixed-wing unmanned air vehicle (UAV) flying at constant altitude is experimentally validated. The overall system is capable of waypoint navigation, threat avoidance, real-time trajectory generation and trajectory tracking. Both the wheeled mobile robot experimental platform and the hierarchical autonomous control software architecture are introduced. Programmed to emulate a fixed-wing UAV flying at constant altitude, a non-holonomic mobile robot is assigned to follow a desired time-parameterised trajectory generated by a real-time trajectory generator to transition through a sequence of targets in the presence of static and popup threats. Hardware results of the autonomous control system where the trajectory tracker applies two velocity controllers accounting for fixed-wing UAV-like input constraints, are compared to simulation results of dynamic controllers that are based on non-smooth backstepping to demonstrate the effectiveness of the overall system.

Trajectory tracking control for a miniature fixed-wing unmanned air vehicle

This article considers the problem of trajectory tracking control for a miniature fixed-wing unmanned air vehicle (UAV). With the UAV equipped with longitudinal and lateral autopilots, we adopt a kinematic model that takes into account the fact that the heading of the UAV is controlled by its roll motion and the autopilot responses to air speed and roll control commands are first order in nature. Backstepping techniques are applied to derive air speed and roll control commands from known air speed and heading control laws that explicitly account for air speed and heading rate constraints of the UAV. Regarding inaccurately known autopilot constants, a parameter adaptation technique is used to estimate autopilot constants. High-fidelity simulation results on a six degree-of-freedom (DOF) 12-state fixed-wing UAV model are presented to show the effectiveness of our approach.

On Constrained Nonlinear Tracking Control of a Small Fixed-wing UAV

The problem of constrained nonlinear tracking control for a small fixed-wing unmanned air vehicles (UAV) is considered. With the UAV equipped with low-level autopilots, the twelve-state model of the UAV is reduced to a six-state model with heading, air speed, and altitude command inputs. Three different approaches based on the state dependent Riccati equation (SDRE), Sontag's formula, and aggressive selection from a satisficing control set are proposed to design the heading and air speed control commands. Those approaches are compared with each other graphically to show their strength and weakness under different scenarios. High-fidelity simulation results on a six-degree-of-freedom twelve-state fixed-wing UAV model are presented to demonstrate the performance of the three approaches.

Differential Geometric Path Planning of Multiple UAVs

Safe and simultaneous arrival of constant speed, constant altitude unmanned air vehicles (UAVs) on target is solved by design of paths of equal lengths. The starting point for our solution is the well-known Dubins path, which is composed of circular arc and line segments, thus requiring only one simple maneuver—constant rate turn. An explicit bound can be imposed on the rate during the design and the resulting paths are the minimum time solution of the problem. However, transition between arc and line segments entails discontinuous changes in lateral acceleration (latax), making this approach impractical for real fixed wing UAVs. Therefore, we replace the Dubins solution with a novel one, based on quintic Pythagorean hodograph (PH) curves, whose latax demand is continuous. The PH paths are designed to have lengths close to the lengths of the Dubins paths to stay close to the minimum time solution. To derive the PH paths, the Dubins solution is first interpreted in terms of differential geometry of curves using the path length and curvature as the key parameters. The curvature of a Dubins path is a piecewise constant and discontinuous function of its path length, which is a differential geometric expression of the discontinuous latax demand involved in transitions between the arc and the line segment. By contrast, the curvature of the PH path is a fifth order polynomial of its path length. This is not only continuous but also has enough design parameters (polynomial coefficients) to meet the latax (curvature) constraints (bounds) and make the PH solution close to the minimum time one. The solution involves the design of paths meeting the curvature constraint and is followed by producing multiple paths of equal length by increasing the lengths of the shorter paths to match the longest one. The safety constraint, intercollision avoidance is achieved by satisfying two conditions: minimum separation distance and nonintersection at equal distance. The offset curves of the PH path are used to design a safety region along each path.

Fault tolerant formation flight control of UAVs

In this paper, we summarise our recent results in fault tolerant formation control of Unmanned Air Vehicles (UAV). A fault tolerant control scheme to deal with both GPS sensor failure and wireless communication packet losses is presented. Moreover, some extensions to the formation control algorithms developed by UC Berkeley are made to support time-varying heading and curved flight trajectories. The effectiveness of the presented fault tolerant control scheme is illustrated by real-time formation flight simulations conducted in a wireless network environment. Both rotary and fixed wing UAVs, mesh and triangular formations, and straight and curved trajectories are considered in our real-time simulations.