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Nonlinear optimal control for aircraft ground manoeuvres

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posted on 02.07.2019, 13:45 authored by Zexin Huang
Despite recent advances in flight control systems, aircraft ground manoeuvres are still conducted manually. This thesis aims to improve the efficiency and safety of airport operations by developing a real-time optimal controller for
ground operations, especially high-speed runway turnoff. A reliable and robust controller is able to improve airport traffic capacity and reduce runway events of incursion, excursion, and confusion. A high-fidelity fully-parameterised aircraft model is developed to capture aircraft ground dynamics. The nonlinearities enter the system via sub-models of tyres and aerodynamics. A numerical continuation method is used to compute and track steady-state solutions under the variation of parameters, providing a global picture of the system stability within a typical operation envelop. Dynamic simulations are carried out to analyse transient behaviours
which are not captured by the bifurcation analysis. Three controllers are employed to investigate the automation of aircraft runway exit manoeuvres. An Expert Pilot Model is developed to represent manoeuvres that are manually operated by pilots. To evaluate the optimality of the proposed Expert Pilot Model (EPM), Generalised Optimal Control (GOC) is employed to numerically investigate the optimal solutions for aircraft runway exit manoeuvres. A formal solution of real-time optimal steering control problem is desired in light of the gap between the Expert Pilot Model
and Generalised Optimal Control. Therefore, Predictive Steering Control is developed based on Linear Quadratic method with lookahead, which is able to deliver near-optimal manoeuvres.



  • Aeronautical, Automotive, Chemical and Materials Engineering


  • Aeronautical and Automotive Engineering


Loughborough University

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© Zexin Huang

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A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy at Loughborough University.




James Knowles ; Matt Best

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