Flight Trajectory Optimization of Sailplane After Rope Break

2021 ◽  
pp. 1-13
Author(s):  
Armando R. Collazo Garcia ◽  
Prateek Ranjan ◽  
Kevin J. Chen ◽  
Kai A. James ◽  
Phillip J. Ansell
Keyword(s):  
Trajectory Optimization ◽  
Flight Trajectory

Geographical area selection and construction of a corresponding routing grid used for in-flight management system flight trajectory optimization

2016 ◽  
Vol 231 (5) ◽  
pp. 809-822
Author(s):  
Bogdan D Dancila ◽  
Ruxandra M Botez
Keyword(s):  
Traffic Management ◽  
Trajectory Optimization ◽  
Management System ◽  
Optimization Algorithms ◽  
Geographical Area ◽  
Atmospheric Conditions ◽  
Flight Trajectory ◽  
Trajectory Data ◽  
Design Variables ◽  
Grid Nodes

This paper proposes a new method for selecting an ellipse-shaped geographical area and constructing a routing grid that circumscribes the contour of the designated area. The resulting grid describes the set of points used by the flight trajectory optimization algorithms to determine an aircraft’s optimal flight trajectory as a function of given particular atmospheric conditions. This method was developed with the intent of its employment in the context of Flight Management System trajectory optimization algorithms, but can be used in Air Traffic Management environments as well. The routing grid limits the trajectory’s maximal total ground distance (between the departure and destination airports), maximizes the geographical area (for a better consideration of the wind conditions) and minimizes the number of grid nodes. The novelty of the proposed method resides in the fact that it allows a distinct and independent parameterization and control of the ellipse’s total surface, and the required size of the take-off/landing procedure maneuvering areas at the departure/destination airports. The ellipse contour constructed using this method is, therefore, well adapted to the particular configuration of the trajectory for which the optimization is performed. Each design variables’ influence is presented, as well as a set of routing grids generated for trajectories corresponding to different total flight distances, and were further compared with real flight trajectory data retrieved using the website Flight Aware.

Flight Trajectory Optimization to Minimize Ground Noise in Helicopter Landing Approach

2009 ◽  
Vol 32 (2) ◽  
pp. 605-615 ◽  
Author(s):  
Takeshi Tsuchiya ◽  
Hirokazu Ishii ◽  
Junichi Uchida ◽  
Hiroshi Ikaida ◽  
Hiromi Gomi ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Flight Trajectory ◽  
Helicopter Landing ◽  
Ground Noise

New atmospheric data model for constant altitude accelerated flight performance prediction calculations and flight trajectory optimization algorithms

2020 ◽  
pp. 095441002094555
Author(s):  
Radu I Dancila ◽  
Ruxandra M Botez
Keyword(s):  
Performance Prediction ◽  
Data Model ◽  
Trajectory Optimization ◽  
Computation Time ◽  
Atmospheric Parameter ◽  
Flight Performance ◽  
Flight Trajectory ◽  
Proposed Model ◽  
Atmospheric Data ◽  
Constant Altitude

This article presents a new method for storing and computing the atmospheric data used in time-critical flight trajectory performance prediction calculations, such as flight performance prediction calculations in flight management systems and/or flight trajectory optimization, of constant altitude cruise segments. The proposed model is constructed based on the forecast data provided by Meteorological Service Agencies, in a GRIB2 data file format, and the set of waypoints that define the lateral component of the evaluated flight profile(s). The atmospheric data model can be constructed/updated in the background or off-line, when new atmospheric prediction data are available, and subsequently used in the flight performance computations. The results obtained using the proposed model show that, on average, the atmospheric parameter values are computed six times faster than through 4D linear interpolations, while yielding identical results (value differences of the order of 10e−14). When used in flight trajectory performance calculations, the obtained results show that the proposed model conducts to significant computation time improvements. The proposed model can be extended to define the atmospheric data for a set of cruise levels (usually multiple of 1000 ft).

Practice Summary: Flight Trajectory Optimization

2013 ◽  
Vol 43 (6) ◽  
pp. 547-549
Author(s):  
Srinivas Bollapragada ◽  
Joel Klooster ◽  
MacKenzie Cumings
Keyword(s):  
Trajectory Optimization ◽  
Flight Trajectory

Ornithopter Flight Maneuver Control

2009 ◽  
Author(s):  
John M. Dietl ◽  
Ephrahim Garcia
Keyword(s):  
Trajectory Optimization ◽  
Vertical Plane ◽  
Open Loop ◽  
The Body ◽  
Computer Assisted ◽  
Flight Trajectory ◽  
Forward Flight ◽  
Initial State ◽  
Final State ◽  
Power Sources

Ornithopter studies in the past have focused on ornithopter construction, power sources, wing design, maximizing thrust, energy efficiency, steady flight trajectories, and flight stability. The next step is to control unsteady maneuvers: the transition from hovering flight to forward flight, turns, and vertical takeoff and landing. The design of stable trim conditions for forward flight and for hover has been achieved. In forward flight, an ornithopter is configured like a conventional airplane or large bird. Its fuselage is essentially horizontal and the wings heave in a vertical plane. In hover, however, the body pitches vertically so that the wing stroke in the horizontal plane. Thrust directed downward, the vehicle remains aloft while the downdraft envelops the tail to provide enough flow for vehicle control and stabilization. To connect these trajectories dynamically is the goal. This study of the transition from forward flight to hovering uses two approaches: to first achieve adequate trajectories, and then optimal trajectories. The object is to connect an initial state—in this case forward flight—and a final state—a steady hover at a designated point—through a feasible flight trajectory. A simple approach is to immediately switch between feedback controllers that regulate each trajectory. When the forward flight trajectory approaches the desired location, the computer switches to a control law that regulates the desired hovering trajectory, which—barring instability—should cause the vehicle to settle. A second approach is to select a range of intermediate trims to stabilize. Starting with the full forward speed, the controller will successively stabilize a trim with lower forward velocity. After a finite number of controllers, the system will achieve a stable hover. This approach would lessen the jump between trim conditions, increasing the likelihood of a stable transition. A third approach is to establish an open-loop trajectory through a trajectory optimization algorithm—optimized for shortest altitude drop, shortest stopping distance, or lowest energy consumption. This path itself could be stabilized. This serves to establish the feasibility of new maneuvers in mechanical flapping flight. It also will make it easier to perform the maneuvers by computer assisted control or by providing an example for a pilot to use.

Energy-aware 3D Leader-Follower Flight Trajectory Optimization for Fixed-Wing Aircraft

2022 ◽  
Author(s):  
Praveen Ranjan ◽  
Johnathan Votion ◽  
Yongcan Cao ◽  
Dzung M. Tran ◽  
David Casbeer ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Flight Trajectory ◽  
Energy Aware
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