Precision parafoil recovery - Providing flexibility for battlefield UAV systems?

Wyllie, Tim; Downs, P.

doi:10.2514/6.1997-1497

Cited by 4 publications

(5 citation statements)

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“…Moreover, ram-air parafoils are nowadays considered a vital element of the unmanned air vehicles (UAVs) capability and of International Space Station (ISS) crew rescue vehicle. [4][5][6][7][8][9][10][11][12] Autonomous parafoil capability implies delivering the system to a desired landing point from an arbitrary release point using onboard computer, sensors and actuators. This requires development of a guidance, navigation and control (GNC) system.…”

Section: Introductionmentioning

confidence: 99%

Development of Control Algorithm for the Autonomous Gliding Delivery System

Kaminer

Yakimenko

2003

17th AIAA Aerodynamic Decelerator Systems Technology Conference and Seminar

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Abstract. The paper considers the development and simulation testing of the control algorithms for an autonomous high-glide aerial delivery system, which consists of 650sq.ft rectangular double-skin parafoil and 500lb payload. The paper applies optimal control analysis to the real-time trajectory generation. Resulting guidance and control system includes tracking this reference trajectory using a nonlinear tracking controller. The paper presents the description of the algorithm along with simulation results and ends with guidelines for the further implementation of the developed software aboard the real system.

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Section: Introductionmentioning

confidence: 99%

Development of Control Algorithm for the Autonomous Gliding Delivery System

Kaminer

Yakimenko

2003

17th AIAA Aerodynamic Decelerator Systems Technology Conference and Seminar

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“…In (1) and (2), m p and J p are the mass and inertia matrix of the parafoil canopy, respectively; V p and W p are the velocity and angular velocity of the parafoil canopy in the parafoil body reference frame; F aerop and M aerop are the parafoil aerodynamic force and moment; F am and M ai are the apparent mass force and inertia moment; G p is the gravity of the parafoil canopy in the parafoil body reference frame; n is the number of suspension lines; the vector T p,i represents the force of each suspension line; the vector l p,i represents the position vector from the mass center of the parafoil canopy to the connection points P1, P2, P3. .…”

Section: Parafoil-uav System Modelmentioning

confidence: 99%

“…Hence, parafoil systems are well suited for fixed-wing unmanned aerial vehicles (UAV) that need to land on unprepared terrain accurately [1]. In recent years, this type of system has been used in several UAVs, including Developmental Sciences Corp.'s SkyEye, Israel Aerospace Industries' Eyeview and NASA's X-38 [2], [3]. However, the parafoil-UAV system has a unique issue called the pendulumswing problem.…”

Section: Introductionmentioning

confidence: 99%

A Multivariate Optimal Control Strategy for the Attitude Tracking of a Parafoil-UAV System

Zhao

2020

IEEE Access

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The pendulum-swing problem is a factor that limits the development of parafoil-unmanned aerial vehicle (UAV) systems. Autonomous attitude control based on parafoil and UAV control mechanisms is considered an effective solution to this problem. However, due to the coupling effect of the two control mechanisms, conventional control methods are not suitable. The design of attitude control for parafoil-UAV systems has become a challenge. For this problem, a model-independent optimal control method called multivariate extremum seeking with the Newton method (ES-NM) is introduced in this paper. To assess the performance of multivariate ES-NM control for parafoil-UAV systems, a multibody dynamic model based on the flexible line assumption is built. The aerodynamic coefficients of this model are estimated via computational fluid dynamics (CFD) and corrected using flight data. Using this model, the coupling effect of the two control mechanisms is investigated, and the control range is determined. Finally, the effectiveness of multivariate ES-NM controller for a parafoil-UAV system is verified. Simulation experiments performed under various conditions demonstrate that the multivariate ES-NM control can manipulate the UAV control mechanism and the parafoil control mechanism simultaneously and produce the desired UAV attitude track. Additionally, comparisons to proportional-integral-derivative (PID) control reveal the better performance of the proposed control method. INDEX TERMS Parafoil-UAV system, nonlinear multibody dynamic model, multivariate ES-NM control, attitude optimal control, attitude tracking.

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“…reference frame to the parafoil canopy reference frame. The matrix can be written as given in (3), as shown at the top of this page.…”

Section: A Parafoil Canopy Dynamic Modelmentioning

confidence: 99%

“…They can perform turning maneuvers in the air and impact the ground at low speed by asymmetric and symmetric deflections of the parafoil trailing edge. These systems have been used in Development Science Corp.'s Skyeye, Israel Aerospace Industries' Eyeview and NASA's X-38 [3], [4].…”

Section: Introductionmentioning

confidence: 99%

An Improved Nonlinear Multibody Dynamic Model for a Parafoil-UAV System

Zhao

2019

IEEE Access

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A recovery system for an unmanned aerial vehicle (UAV) using a steerable parafoil is an attractive concept. However, due to the complex interaction between the parafoil and the UAV, this parafoil system has not seen widespread use in the UAV recovery. Under the influence of the UAV, the suspension lines of the system are not always tight, so most of the existing models do not work. To analyze the parafoil and UAV interaction when the suspension lines are tight or slack, this study presents a method for improving a multibody dynamic model for a parafoil-UAV system. The parafoil and UAV are modeled as usual, while the suspension lines are modeled as a combination of several linear viscoelastic elements. All models are coupled, and the nonlinear equations of motion are then derived. To analyze the influence of the invalid suspension lines, this improved model has been compared with an 8-degrees of freedom model. The comparisons demonstrate that the simulation results of the improved model and the 8-DoF model are similar under a small control input. However, under a large control input, the results become significantly different. In an actual flight test, the accuracy of this improved model is found to be better than the 8-DoF model. Finally, an attitude optimal control system is designed for this improved model. The performance of this autonomous control is presented at the end of this paper.INDEX TERMS Parafoil-UAV system, parafoil and UAV interaction, nonlinear multibody dynamic model, flexible line model, attitude optimal control.

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Precision parafoil recovery - Providing flexibility for battlefield UAV systems?

Cited by 4 publications

References 0 publications

Development of Control Algorithm for the Autonomous Gliding Delivery System

Development of Control Algorithm for the Autonomous Gliding Delivery System

A Multivariate Optimal Control Strategy for the Attitude Tracking of a Parafoil-UAV System

An Improved Nonlinear Multibody Dynamic Model for a Parafoil-UAV System

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