Position Locking for Permanent Magnet Synchronous Machine Propeller Drives in Drones by Hall-Effect Sensor-Assisted Nonlinear Observer

The paper presents a hall-effect sensor-assisted non-linear observer-based solution for position locking of a surface-mounted permanent magnet synchronous motor (SMPMSM) propeller drive in drone applications. The purpose of the position locking is to ensure a fixed motor position at the landing instant to avoid mechanical damage to the propeller. To evaluate the proposed solution, the position locking sequence of the motor drive is studied for two cases, implemented with two different state machines. The first case is relying on an encoder to provide the position feedback signal and serves as a reference for assessing the performance of the proposed solution based on the position estimate from the hall-effect sensor-assisted nonlinear observer. Experimental results show how the proposed solution can provide sufficient performance of position locking without the encoder.Position Locking for Permanent Magnet Synchronous Machine Propeller Drives in Drones by Hall-Effect Sensor-Assisted Nonlinear ObserveracceptedVersio

High Angle of Attack Landing of an Unmanned Aerial Vehicle

Motivated by the limited landing space on board a ship, this thesis investigates the landing of the Skywalker X8 fixed wing unmanned aerial vehicle (UAV) in a net. Further motivated by the way birds abruptly, and equally elegantly, reduce their velocity when landing on a perch or the branch of a tree, a perched landing strategy utilizing the increased drag experienced for large angles of attack is used to minimize the velocity at impact with the net. This is accomplished by expressing landing as an optimal control problem, taking advantage of a nonlinear model of the X8 that is valid for high angles of attack. At this stage, the optimal control problem is only concerned with the three longitudinal degreesof- freedom. It is solved in an open source optimization framework, using a nonlinear interior point method. Further, a nonlinear model predictive controller (NMPC) that can control the X8 throughout the landing is developed. At the heart of the optimal control problem lies a linear model, blended with a flat plate model to increase its validity for high angles of attack in lift, drag and pitch moment. The linear model is developed using an easy-to-use computational fluid dynamics (CFD) modeling software. In addition a six degrees-of-freedom software-in-the-loop (SITL) simulator is developed for future use in testing of hardware-near implementations of the controller, and to allow for validation of the model through pilot testing. Comparison of six different landing scenarios yield a wide range of landing velocities, depending on the constraints of the scenario. Simulations with the developed NMPC show that the same performance is achievable through control of the X8 under minor environmental disturbances. From this it is concluded that the perched landing strategy will lead to a considerable reduction in terminal absolute velocity, compared to a low angle of attack approach. It is found to be advantageous to start from a low altitude, landing into an elevated net. However, whether an equally large reduction is possible in practice depends on the capabilities of the real-time implementation and the validity of the model, particularly the propeller model, the pitching moment and drag coefficients. Finally it depends on how the lateral degrees-of-freedom are affected by the high angle of attack flight

Precision control of fixed-wing UAV and robust navigation in GNSSdenied environments

Unmanned aerial vehicles (UAVs) have been adopted to a wide range of applications, but fully autonomous flight is still utopian, especially for safety-critical applications. This thesis seeks to close this gap by mainly considering robust navigation and precision control. Navigation systems of safety-critical unmanned aircraft need an alternative position aiding source to global navigation satellite system (GNSS), as it is vulnerable to naturally occurring disturbances, such as ionospheric scintillation, and to malicious disturbances. Two promising alternatives, are position measurements from ultrawideband radio beacons and phased-array radio systems. Tight integration of ultra wideband (UWB) range measurements with real-time kinematic (RTK) aiding of inertial navigation for increased robustness to GNSS dropouts, is achieved using a double-differenced nonlinear observer. The results are verified using a simulated unmanned aerial vehicle (UAV) with realistic inertial, GNSS and UWB measurements. The phased-array-radio-based navigation system consists of a multiplicative extended Kalman filter that utilize these measurements, along with an exogenous altitude measurement, to provide corrections to the inertial navigation system, and performs measurement outlier rejection to mitigate effects of radio measurement reflections. In addition to providing a positioning solution, the navigation system make magnetometers and magnetic compasses made superfluous during flight, by providing heading estimates. The accuracy, reliability and versatility of the navigation system are demonstrated through three series of experiments. First, experimental results obtained from a multirotor and a fixed-wing UAV flight are presented, showing a 14% improvement in root-mean-square error compared to previous results. Then an online guidance, navigation and control system, based on the navigation system is demonstrated in beyond-visual-line-of-sight flights in controlled airspace, with a fixed-wing UAV, without the use of GNSS. More precise control can enable the use of fixed-wing UAVs in a wider range of applications, in particular landing, without the use of a skilled remote control pilot. Commercial-off-the-shelf autopilots are reliable, given their extensive use and testing, and some even provide automatic landing capabilities. They are, however, not sufficient for automatic recovery in moving arrest systems, such as nets, which are simple infrastructures that can be installed in crammed or remote locations, such as aboard ships. Under general assumptions on the autopilot, it is extended by automatic plan generation, line-of-sight guidance along moving lines and enhanced RTK-GNSS positioning relative to the net, in a modular, non-intrusive manner to remain reliable. The system is demonstrated by two series of experiments; in a stationary net, to demonstrate controller performance, and in a manually moving net, to demonstrate compensation of arrest system motion. Another landing strategy is through deep-stall, where the large increase in aerodynamic drag during stall is used to significantly reduce the speed, and thus impact, of the UAV during landing. One way to increase the precision compared to existing solutions, is through the presented nonlinear model predictive controller, which use a six degree of freedom model of the UAV to determine control surface deflections that will steer it to a desired landing location, along a predetermined decent angle, while minimizing speed and respecting dynamic and actuator constraints. An extensive simulation study shows that the controller handles a large span of wind speeds, but is sensitive to wind gusts. To enable operation in a wider range of conditions, path following for fixed-wing UAVs should emphasize mitigation of wind effects, which at the very least implies a formulation using course angles. In this thesis, this is achieved by basing the guidance law on the coordinated turn equation, which is derived in in a general form for completeness, to ensure that no effects are unintentionally ignored. By cascading the coordinated-turn based controller with a line-of-sight guidance law, uniform semiglobal exponential stability of the cross-track error and course angle is proven. The controller is easy to tune, in terms of damping ratio and bandwidth. Through a comparative simulation study to the state-of-the-art, four guidance laws based on the analysis are shown to reduce the maximum cross-track error by 10% in wind. The system shows merit through an experimental verification. Mathematical models of UAVs can be used both to obtain higher precision control, through model-based control techniques, to improve robustness, through e.g. fault detection, and to cut development time, cost and risk, through a simulator. For this reason, a complete six degrees-of-freedom UAV model is presented, based on a combination of wind tunnel testing and numeric analysis for the aerodynamic model, wind tunnel testing for the propulsion model, and bifilar pendulum testing to identify moments of inertia

Control System Architecture for Automatic Recovery of Fixed-Wing Unmanned Aerial Vehicles in a Moving Arrest System

Automatic recovery is an important step in enabling fully autonomous missions using fixed-wing unmanned aerial vehicles (UAVs) operating from ships or other moving platforms. However, automatic recovery in moving arrest systems is only briefly studied in the research literature, and is not yet an option when using low-cost, commercial off-the-shelf (COTS) autopilots. Acknowledging the reliability and low cost of COTS avionics, this paper adds recovery functionality as a modular extension based on non-intrusive additions to an autopilot with very general assumptions on its interface. This is achieved by line-of-sight guidance, which sends an augmented desired position to the autopilot, to ensure line-following along a virtual runway that guides the UAV into the arrest system. The translation and rotation of this line is determined by the pose of the arrest system, determined using two Global Navigation Satellite System (GNSS) receivers, where one is configured as a Real-Time Kinematic (RTK) base station. The relative position of the UAV and arrest system is also precisely estimated using RTK GNSS. Through extensive field testing, on two different fixed-wing UAVs, the system has shown its performance and reliability; 43 recovery attempts in a stationary net hit 0.01 ± 0.25m to the right and 0.07 ± 0.20m below the target in calm conditions. Further, 15 recoveries in a barge-mounted, ship-towed net hit 0.06 ± 0.53m to the right and 0.98 ± 0.27m below the target in winds up to 4 m/s. The remaining error is largely systematic, caused by communication delays, and could be reduced with more integral effect or through direct compensation

LPV model reference control for fixed-wing UAVs

This paper proposes a linear parameter varying (LPV) model reference-based control for fixed-wing unmanned aerial vehicles (UAVs), which achieves agile and high performance tracking objectives in extended flight envelopes, e.g. when near stall or deep stall flight conditions are considered. Each of the considered control loops (yaw, pitch and airspeed) delivers an error model that can be reshaped into a quasi-LPV form through an appropriate choice of the scheduling variables. The quasi-LPV error models are suitable for designing error feedback controllers using linear matrix inequalities (LMIs), which are derived within the quadratic Lyapunov framework. Simulation results are used to show the effectiveness of the proposed approach

LPV model reference control for fixed-wing UAVs

This paper proposes a linear parameter varying (LPV) model reference-based control for fixed-wing unmanned aerial vehicles (UAVs), which achieves agile and high performance tracking objectives in extended flight envelopes, e.g. when near stall or deep stall flight conditions are considered. Each of the considered control loops (yaw, pitch and airspeed) delivers an error model that can be reshaped into a quasi-LPV form through an appropriate choice of the scheduling variables. The quasi-LPV error models are suitable for designing error feedback controllers using linear matrix inequalities (LMIs), which are derived within the quadratic Lyapunov framework. Simulation results are used to show the effectiveness of the proposed approach

Phased Array Radio Navigation System on UAVs: GNSS-based Calibration in the Field

With global coverage, high accuracy, and lightweight receivers, global navigation satellite system (GNSS) has been the major positioning solution for unmanned aerial vehicles (UAV). However, GNSS is prone to electromagnetic interference and malicious attacks such as jamming or spoofing due to its low signal-to-noise ratio (SNR). To ensure the continuity and safety of UAV operation, the use of redundant navigation systems is crucial. Phased array radio system (PARS) has proven its potential as a local navigation solution in the last few years. PARS is robust against malicious attacks due to a significantly higher SNR than GNSS together with directional and encrypted transmission. One of the challenges of the PARS-based navigation is the radio antenna at ground station, as its orientation needs to be determined precisely to obtain accurate navigation solution for unmanned vehicles. This paper presents an automatic calibration algorithm for the ground radio antenna orientation using a multiplicative extended Kalman filter (MEKF) based on GNSS and PARS measurements. The calibration algorithm was tested with data obtained from a field test using a fixed wing UAV and validated by a residual analysis comparing the PARS- and GNSS-based positioning

Impact of atmospheric icing on UAV aerodynamic performance

This paper presents a first assessment on the impact of atmospheric icing on the aerodynamic performance of fixed-wing UAVs. Numerical simulations were performed in order to evaluate the impact on lift and drag on a 2D airfoil for UAVs. The results show clear evidence that icing increases drag while decreasing lift and the maximum angle of attack. All these effects have negative impact on the maneuverability, stall behavior, range and general operational capabilities of UAVs. Additionally, these results were used in a flight simulator in order to allow the simulation of UAV flights in icing conditions and to study the impact of icing on energy consumption and autopilot responses. Results from the flight simulator show higher angles of attack and higher energy consumption when flying in icing conditions. This flight simulator provides a testbed for further research into in-flight ice detection for fixed-wing UAVs

Aided Inertial Navigation of Small Unmanned Aerial Vehicles Using an Ultra-Wideband Real Time Localization System

This paper presents an ultra-wideband (UWB) radio aided inertial navigation system (INS), estimating position, velocity and attitude (PVA), based on a low-cost microelectro-mechanical system (MEMS) Inertial Measurement Units (IMUs). This ensures that a drift free INS is available for local unmanned aerial vehicle (UAV) navigation independent of global navigation satellite systems (GNSS). The experimental results show that the presented integration of UWB and INS is promising for navigating independent of satellite-based positioning systems, and illustrates the possible enhancements that are possible when adding an additional vertical position measurement.acceptedVersion© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Impact of Atmospheric Icing on UAV Aerodynamic Performance

This paper presents a first assessment on the impact of atmospheric icing on the aerodynamic performance of fixed-wing UAVs. Numerical simulations were performed in order to evaluate the impact on lift and drag on a 2D airfoil for UAVs. The results show clear evidence that icing increases drag while decreasing lift and the maximum angle of attack. All these effects have negative impact on the maneuverability, stall behavior, range and general operational capabilities of UAVs. Additionally, these results were used in a flight simulator in order to allow the simulation of UAV flights in icing conditions and to study the impact of icing on energy consumption and autopilot responses. Results from the flight simulator show higher angles of attack and higher energy consumption when flying in icing conditions. This flight simulator provides a testbed for further research into in-flight ice detection for fixed-wing UAVs