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A Hybrid Optimal Control Approach to Maximum Endurance of Aircraft


A Hybrid Optimal Control Approach to Maximum Endurance of Aircraft

Oelberg, Emily (2018) A Hybrid Optimal Control Approach to Maximum Endurance of Aircraft. Masters thesis, Concordia University.

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Aircraft performance optimization is a field of increasing interest, especially with the prevalent use of flight management systems (FMS) on commercial aircraft, as well as the growing field of autonomous aircraft. This thesis addresses the maximum endurance performance mode. Maximizing the endurance of an aircraft has several applications in data collection, surveillance, and commercial flights. Each of these applications may be best suited for different aircraft such as fixed-wing or quad-rotor vehicles, with power plants being either fuel-burning or electric.

The objectives of this thesis are to solve the maximum endurance problem using an optimal control framework for fixed-wing aircraft while developing a unified model of energy-depletion which encompasses both fuel-burning and all-electric aircraft. The unified energy-depletion model allows the results to be applied to turbojet, turbofan, turboprop, and all-electric aircraft. The problem of maximum endurance in cruise will be solved for a three-phase model of flight including climb, cruise, and descent. This problem is solved using a hybrid optimal control framework using a unified energy-depletion model.

One of the advantages of using an optimal control framework is the possibility to develop analytical solutions. The results of this thesis include a general solution for maximizing the endurance of fixed-wing aircraft, as well as specific analytical solutions for each aircraft configuration wherever possible. Some benefits of analytical solutions are that they require the least amount of computation time and provide insight into the problem including sensitivities and physical dependencies. Simulations are provided to validate the results in the case of specific aircraft configurations (turbojet, turbofan, turboprop, and all-electric).

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Oelberg, Emily
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:10 August 2018
Thesis Supervisor(s):Rodrigues, Luis
ID Code:984151
Deposited On:16 Nov 2018 16:16
Last Modified:16 Nov 2018 16:16
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