Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Coates, Erlend M.; Fossen, Thor I.

doi:10.3390/app11073147

Cited by 11 publications

(5 citation statements)

References 88 publications

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“…The angle of attack α time history in Figure 4a reveals that exclusive use of a positive elevator deflection (PC 1) caused an initial decrease in angle of attack as expected. Similar results have been obtained in [141,142] for tailless aircraft. The deflection of the elevator causes a change in the camber of the airfoil of the wing and consequently changes the lift coefficient.…”

Section: Pitch Attitude Controlsupporting

confidence: 88%

Modeling and Control of an Articulated Multibody Aircraft

2022

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Insects use dynamic articulation and actuation of their abdomen and other appendages to augment aerodynamic flight control. These dynamic phenomena in flight serve many purposes, including maintaining balance, enhancing stability, and extending maneuverability. The behaviors have been observed and measured by biologists but have not been well modeled in a flight dynamics framework. Biological appendages are generally comparatively large, actuated in rotation, and serve multiple biological functions. Technological moving masses for flight control have tended to be compact, translational, internally mounted and dedicated to the task. Many flight characteristics of biological flyers far exceed any technological flyers on the same scale. Mathematical tools that support modern control techniques to explore and manage these actuator functions may unlock new opportunities to achieve agility. The compact tensor model of multibody aircraft flight dynamics developed here allows unified dynamic and aerodynamic simulation and control of bioinspired aircraft with wings and any number of idealized appendage masses. The demonstrated aircraft model was a dragonfly-like fixed-wing aircraft. The control effect of the moving abdomen was comparable to the control surfaces, with lateral abdominal motion substituting for an aerodynamic rudder to achieve coordinated turns. Vertical fuselage motion achieved the same effect as an elevator, and included potentially useful transient torque reactions both up and down. The best performance was achieved when both moving masses and control surfaces were employed in the control solution. An aircraft with fuselage actuation combined with conventional control surfaces could be managed with a modern optimal controller designed using the multibody flight dynamics model presented here.

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Section: Pitch Attitude Controlsupporting

confidence: 88%

Modeling and Control of an Articulated Multibody Aircraft

2022

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“…In this section, we demonstrate the efficacy of our experimental platform by presenting some of our results, with a special focus on the switching mechanism. In particular, we show initial results for GAC, based on [21], and look at one of our earliest attempts at closed-loop flight using DRL.…”

Section: Resultsmentioning

confidence: 99%

“…In this section, we describe the main control algorithms evaluated in the Autofly project, namely NMPC [19], DRL [20], GAC [21], as well as a proportional-integralderivative (PID) benchmark implementation based on the ArduPilot [1] fixed-wing attitude controller. The capabilities needed to effectively run these algorithms online define the requirements for the system architecture presented in Section III.…”

Section: Control Algorithms: Overviewmentioning

confidence: 99%

“…The capabilities needed to effectively run these algorithms online define the requirements for the system architecture presented in Section III. This section also provides the necessary background for the experimental results of Section V. An in-depth discussion of the experimental controllers is out of scope of this work and more details can be found in each of the respective references [19], [20], [21]. A comparison of the most significant features of the controllers is given in Tab.…”

Section: Control Algorithms: Overviewmentioning

confidence: 99%

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Toward Nonlinear Flight Control for Fixed-Wing UAVs: System Architecture, Field Experiments, and Lessons Learned

Coates

Reinhardt

Gryte

et al. 2022

2022 International Conference on Unmanned Aircraft Systems (ICUAS)

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Inner-loop control algorithms in state-of-the-art autopilots for fixed-wing unmanned aerial vehicles (UAVs) are typically designed using linear control theory, to operate in relatively conservative flight envelopes. In the Autofly project, we seek to extend the flight envelopes of fixed-wing UAVs to allow for more aggressive maneuvering and operation in a wider range of weather conditions. Throughout the last few years, we have successfully flight tested several inner-loop attitude controllers for fixed-wing UAVs using advanced nonlinear control methods, including nonlinear model predictive control (NMPC), deep reinforcement learning (DRL), and geometric attitude control. To achieve this, we have developed a flexible embedded platform, capable of running computationally demanding lowlevel controllers that require direct actuator control. For safe operation and rapid development cycles, this platform can be deployed in tandem with well-tested standard autopilots. In this paper, we summarize the challenges and lessons learned, and document the system architecture of our experimental platform in a best-practice manner. This lowers the threshold for other researchers and engineers to employ new low-level control algorithms for fixed-wing UAVs. Case studies from outdoor field experiments are provided to demonstrate the efficacy of our research platform.

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“…Tests of coverage paths it can be conducted with drones in a real or simulated environment. The most viable option for this stage of the work is simulation, as verified by other research [69][70][71][72]. Simulation has been recognized as an important research tool; initially, simulation was an academic research tool, but with the advancement of computers, simulation has reached new levels.…”

Section: Introductionmentioning

confidence: 97%

Coverage Path Planning with Semantic Segmentation for UAV in PV Plants

et al. 2021

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Solar energy is one of the most strategic energy sources for the world’s economic development. This has caused the number of solar photovoltaic plants to increase around the world; consequently, they are installed in places where their access and manual inspection are arduous and risky tasks. Recently, the inspection of photovoltaic plants has been conducted with the use of unmanned aerial vehicles (UAV). Although the inspection with UAVs can be completed with a drone operator, where the UAV flight path is purely manual or utilizes a previously generated flight path through a ground control station (GCS). However, the path generated in the GCS has many restrictions that the operator must supply. Due to these restrictions, we present a novel way to develop a flight path automatically with coverage path planning (CPP) methods. Using a DL server to segment the region of interest (RoI) within each of the predefined PV plant images, three CPP methods were also considered and their performances were assessed with metrics. The UAV energy consumption performance in each of the CPP methods was assessed using two different UAVs and standard metrics. Six experiments were performed by varying the CPP width, and the consumption metrics were recorded in each experiment. According to the results, the most effective and efficient methods are the exact cellular decomposition boustrophedon and grid-based wavefront coverage, depending on the CPP width and the area of the PV plant. Finally, a relationship was established between the size of the photovoltaic plant area and the best UAV to perform the inspection with the appropriate CPP width. This could be an important result for low-cost inspection with UAVs, without high-resolution cameras on the UAV board, and in small plants.

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Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Cited by 11 publications

References 88 publications

Modeling and Control of an Articulated Multibody Aircraft

Modeling and Control of an Articulated Multibody Aircraft

Toward Nonlinear Flight Control for Fixed-Wing UAVs: System Architecture, Field Experiments, and Lessons Learned

Coverage Path Planning with Semantic Segmentation for UAV in PV Plants

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