Flight Test Results for Glide Slope Control of Parafoil Canopies of Various Aspect Ratios

Ward, Michael B.; Gavrilovski, Alek; Costello, Mark

doi:10.2514/6.2011-2620

Cited by 16 publications

(9 citation statements)

References 9 publications

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“…The achievable turn rate for any PADS has a practical limit, since a steep turn rate could induce spiral divergence. For a vehicle with similar characteristics as the simulated in this study, Ward et al [ 39 , 40 ] report maximum turn rates from 15 deg/s up to 25 deg/s, depending on the flight mode and control scheme. For the case of larger parafoil-payload vehicles, Lingard [ 11 ] reports a maximum constant turn rate of

deg/s for a canopy with 30 m of wingspan.…”

Section: Simulation Resultsmentioning

confidence: 76%

Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems

Garcia-Huerta

González-Jiménez

Villalón-Turrubiates

2020

Sensors

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In this research, we focus on the use of Unmanned Aerial Vehicles (UAVs) for the delivery of payloads and navigation towards safe-landing zones, specifically on the modeling of flight dynamics of lightweight vehicles denoted Precision Aerial Delivery Systems (PADSs). While a wide range of nonlinear models has been developed and tested on high-end applications considering various degrees of freedom (DOF), linear models suitable for low-cost applications have not been explored thoroughly. In this study, we propose and compare two linear models, a linearized version of a 6-DOF model specifically developed for micro-lightweight systems, and an alternative model based on a double integrator. Both linear models are implemented with a sensor fusion algorithm using a Kalman filter to estimate the position and attitude of PADSs, and their performance is compared to a nonlinear 6-DOF model. Simulation results demonstrate that both models, when incorporated into a Kalman filter estimation scheme, can determine the flight dynamics of PADSs during smooth flights. While it is validated that the double integrator model can adequately operate under the proposed estimation scheme for up to small acceleration changes, the linearized model proves to be capable of reproducing the nonlinear model characteristics even during moderately steep turns.

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deg/s for a canopy with 30 m of wingspan.…”

Section: Simulation Resultsmentioning

confidence: 76%

Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems

Garcia-Huerta

González-Jiménez

Villalón-Turrubiates

2020

Sensors

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“…These systems were chosen to examine the effect of scale on payload weight shift as a control mechanism. The small system is called the GT-Imp and was flight tested by Ward et al at the Georgia Institute of Technology [27]. The second system was flight tested by NASA for the X-38 program [28].…”

Section: Example Systemmentioning

confidence: 99%

Parafoil Control Using Payload Weight Shift

Ward

Culpepper

Costello

2014

Journal of Aircraft

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“…This minimizes the effect of coupled system uncertainity and ensures a maximum heading deviation from the estimated wind direction. Recent efforts by Ward and Costello [14,29] have also demonstrated the potential for improved glide-slope tracking through both online system identification, and by exploiting the longitudinal control coupling between incidence angle and symmetric brake deflection. To summarize, while the above approaches [14,[27][28][29] take some measures to account for the effect of wind uncertainty on the parafoil landing position, they offer no robustness to interaction with terrain obstacles, and are subject to the fundamental constraining of the solution space imposed by the glide-slope approach paradigm.…”

Section: Literature Reviewmentioning

confidence: 99%

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Ellertson

2016

AIAA Infotech @ Aerospace

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Autonomously guided parafoil systems can deliver supplies and aid to remote, geographically diverse locations, while providing important safety and logistical advantages over ground-based transportation methods. A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into difficult, complex terrain. Parafoil guidance algorithms must be able to generate feasible trajectory solutions to the target location within highly constrained terrain environments and from a wide range of initial conditions. Robustness is critical for successful payload delivery in the presence of uncertain atmospheric wind disturbances.This thesis presents two online trajectory planning algorithms for autonomous parafoil guidance in complex terrain and wind environments. These -algorithms are capable of operating from arbitrary initial conditions, including altitude, and are robust to wind disturbances that may be highly dynamic throughout terminal descent. The first algorithm, known as Analytic CC-RRT, builds upon the framework of chance-constrained rapidly-exploring random trees (CC-RRT). This planner enables fast incremental trajectory construction in cluttered, non-convex environments, while using chance constraints to ensure probabilistic feasibility. The designed costto-go function prioritizes target accuracy and upwind landings through the selection of partial paths that intelligently consider current and reachable future states. A trained multi-class wind uncertainty model is introduced to classify and anticipate the effect of future wind disturbances online. Utilizing this model, robustness to wind variations is achieved via a novel analytic uncertainty sampling technique, allowing the probability of constraint violation to be efficiently evaluated against arbitrary and aggressive terrain.The second algorithm, known as CC-BLG, incorporates the Analytic CC-RRT proactive wind model and uncertainty sampling technique into the optimized BandLimited Guidance (BLG) framework. Through the design of a novel risk-based objective function, CC-BLG trajectories efficiently balance the parafoil performance metrics of landing accuracy and landing speed with the risk of off-nominal terrain 3 collisions caused by future wind disturbances. Proposed extensions to the analytic uncertainty sampling technique are shown to yield enhanced planning robustness by refining the estimation of trajectory risk. Multi-phase CC-BLG path planning enables initialization of parafoil terminal guidance from potentially high altitudes, while discrete reachability set approximation is used to maintain robust obstacle avoidance over disjoint planning horizons.Extensive Monte Carlo simulation analysis demonstrates that the Analytic CC-RRT and CC-BLG algorithms achieve significant improvements in mean and worstcase landing accuracy within complex terrain scenarios relative to the state-of-the-art Band-Limited Guidance (BLG) algorithm. Flight test experiments conducted with a full-scal...

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Flight Test Results for Glide Slope Control of Parafoil Canopies of Various Aspect Ratios

Cited by 16 publications

References 9 publications

Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems

Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems

Parafoil Control Using Payload Weight Shift

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

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