AeroG-LAETA - Associate Laboratory of Energy, Transports and Aeronautics
Permanent URI for this community
The Aeronautics and Astronautics Research Center (AeroG) is dedicated to the research and technology development in the field of Aeronautics and Space, with a view to improving safety and environmental protection, while promoting the socioeconomic growth and the quality of life of citizens. The activities of the AeroG aim at contributing to strengthen the excellence of European science base in the scientific and technological fields of aeronautics and astronautics.
Website AeroG-LAETABrowse
Browsing AeroG-LAETA - Associate Laboratory of Energy, Transports and Aeronautics by Author "Ahmed, Kawser"
Now showing 1 - 4 of 4
Results Per Page
Sort Options
- Generating Time Optimal Trajectory from Predefined 4D waypoint NetworksPublication . Ahmed, Kawser; Bousson, K.The main purpose of this paper is to develop a trajectory optimization method to generate optimal trajectories that minimize aircraft total trip time between the initial and final waypoint in predefined 4D waypoint networks. In this paper, the 4D waypoint networks only consist of waypoints for climb, cruise and descent approach without the take-off and landing approach phases. The time optimal trajectory is generated for three different lengths of flights (short, medium, and long-haul flight) for two different commercial aircraft and considering zero wind condition. The Results about the presented applications show that by flying a time optimal trajectory, which was found by applying a single source shortest path algorithm (Dijkstra’s algorithm), can lead to the reduction of average travel time by 2.6% with respect to the total trip time.
- Nonlinear Time-varying Parameter Estimation from Noisy MeasurementsPublication . Coelho, Milca; Bousson, K.; Ahmed, KawserOnline parameter estimation for time-varying systems is a fundamental part of adaptive control, real-time system monitoring and prediction. A well-known framework for dealing with such a task is the Kalman filtering. Meanwhile Kalman filtering may be cumbersome for some time-critical systems and inappropriate for systems whose stochastic characteristics are not Gaussian. To overcome these shortcomings, a parameter estimation algorithm devised from Sutton’s dynamic learning rate techniques and based on a learning window and forgetting factor criterion has been used. In doing so, the proposed algorithm avoids the need for heuristic choices of the initial conditions and noise covariance matrices required by the Kalman filtering. The performance of the proposed method is demonstrated successfully on a lateral-directional flight dynamics parameter estimation process for an unmanned aerial vehicle through computational simulation.
- Optimal Fuel Saving in 4D Waypoint NetworksPublication . Ahmed, Kawser; Coelho, Milca; Bousson, K.The purpose of this work is to develop a trajectory optimization method that generates a fuel optimal trajectory from a predefined 4D waypoint networks, where the arrival time is specified for each waypoint in the network. A single source shortest path algorithm is presented to generate the optimal flight trajectory that minimizes fuel burn. Generating such trajectories enables the airlines to cope with increasing fuel costs and to reduce aviation induced climate change, as emission is directly related to the amount of fuel burn. Two case studies were considered and the simulation results showed that flying a fuel optimal trajectory based on the proposed algorithm leads to a reduction of average fuel consumption on international flights by 2-4% compared with the conventional trip fuel.
- Spline parameterization based nonlinear trajectory optimization along 4D waypointsPublication . Ahmed, Kawser; Bousson, K.; Coelho, MilcaFlight trajectory optimization has become an important factor not only to reduce the operational costs (e.g.,, fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g.,, emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory optimization, which are no longer efficient. Presently, the 4D trajectory optimization is required in order to cope with the current air traffic management (ATM). This study deals with a cubic spline approximation method for solving 4D trajectory optimization problem (TOP). The state vector, its time derivative and control vector are parameterized using cubic spline interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into nonlinear programming problem (NLP). The proposed method is successfully applied to the generation of a minimum length optimal trajectories along 4D waypoints, where the method generated smooth 4D optimal trajectories with very accurate results.