Browsing by Subject "Trajectory Optimization"

Now showing 1 - 3 of 3
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    Atmospheric Density-Compensating Model Predictive Control for the Targeted Reentry of the HyCUBE Spacecraft Using Drag Modulation
    (2023-11) Hayes, Alex
    HyCUBE is a proposed test platform designed to enable access to large volumes of hypersonic aerothermodynamic flight test data at a low cost by collecting measurements during a targeted atmospheric entry from low Earth orbit. Due to its small form factor, it performs the targeted reentry by controlling the atmospheric drag acting on it as opposed to using a propulsion system. Using drag to control the trajectory of a spacecraft is difficult because of the dependence of the drag force on the atmospheric density which is highly variable, uncertain and difficult to predict. This thesis develops a method for estimating the in-flight density of the atmosphere, which is different than the predicted density used in generating the nominal trajectory of the spacecraft. This information is leveraged within a model predictive control strategy to improve tracking performance, reduce control effort and increase robustness to actuator saturation compared to the state-of-the-art approach. A method is also developed to determine whether a spacecraft that has drifted far from the guidance trajectory is physically capable of recovering, or whether a new guidance must be generated. The estimation and control framework is then tested in a Monte Carlo simulation campaign. These simulation efforts demonstrate that the proposed framework is able to stay within 100 km of the guidance trajectory in 98.4% of cases while the remaining cases were pushed away from the guidance by large density errors that could not be physically compensated for by the drag control device. For the successful cases, the proposed framework was able to guide the spacecraft to the desired location at the entry interface altitude with a mean error of 12.1 km, a maximum error of 142 km, and 99.7% of cases below 100 km. All tracking errors were small enough such that the spacecraft could safely target reentry away from populated areas.
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    An efficient algorithm for commercial aircraft trajectory optimization in the air traffic system.
    (2012-07) Devulapalli, Raghuveer
    A discrete search strategy is presented to determine optimal aircraft trajectories which can be unconstrained or regulated to follow current Air Traffic Control (ATC) procedures. The heuristic based Astar (A*) search algorithm has been selected for its efficiency and its inherent ability to handle numerous constraints as a discrete method. A point-mass aircraft model is assumed to accurately simulate commercial aircraft dynamics for the provided trajectories. The two dimensional space and the states of aircraft have been divided into discrete pieces. To show the effectiveness of the algorithm, two-dimensional vertical and horizontal profile are simulated. Simulation results compare optimal trajectories that range from unconstrained to those that completely adhere to strict ATC procedures. Those trajectories following ATC procedures follow a segmented flight pattern where each segment follows specified objectives, terminating when certain criteria has been met. Trajectories are optimized for a combination of time and fuel with an emphasis on reducing fuel consumption.
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    Practical strategies of wind energy utilization for uninhabited aerial vehicles in loiter flights.
    (2008-12) Singhania, Hong Yang
    Uninhabited Aerial Vehicle (UAV) is becoming increasingly attractive in missions where human presence is undesirable or impossible. Agile maneuvers and long endurance are among the most desired advantages of UAVs over aircraft that have human pilots onboard. Past studies suggest that the performance of UAVs may be considerably improved by utilizing natural resources, especially wind energy, during flights. The key challenge of exploiting wind energy in practical UAV operations lies in the availability of reliable and timely wind field information in the operational region. This thesis presents a practical onboard strategy that attempts to overcome this challenge, to enable UAVs in utilizing wind energy effectively during flights, and therefore to enhance performance. We propose and explore a strategy that combines wind measurement and optimal trajectory planning onboard UAVs. During a cycle of a loiter flight, a UAV can take measurements of wind velocity components over the flight region, use these measurements to estimate the local wind field through a model-based approach, and then compute a flight trajectory for the next flight cycle with the objective of optimizing fuel. As the UAV follows the planned trajectory, it continues to measure the wind components and repeats the process of updating the wind model with new estimations and planning optimal trajectories for the next flight cycle. Besides presenting an onboard trajectory planning strategy of wind energy exploration, estimation, and utilization, this research also develops a semi-analytical linearized solution to the formulated nonlinear optimal control problem. Simulations and numerical results indicate that the fuel savings of trajectories generated using the proposed scheme depend on wind speed, wind estimation errors, rates of change in wind speed, and the wind model structures. For a given wind field, the magnitude of potential fuel savings is also contingent upon UAVs' performance capabilities.