A nonlinear worst-case analysis of an LPV controller for the approach phase of a re-entry vehicle

Menon, Prathyush, Prempain, Emmanuel, Postlethwaite, Ian, Bates, Declan and Bennani, Samir (2009) A nonlinear worst-case analysis of an LPV controller for the approach phase of a re-entry vehicle. In: Proceedings of the AIAA Guidance, Navigation, and Control Conference:. American Institute of Aeronautics and Astronautics, Reston, VA, USA. ISBN 978-1600869785

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.2514/6.2009-5638

Abstract

In this paper, a nonlinear robustness analysis of an LPV controller for the approachphase of a re-entry vehicle is presented. The nonlinear longitudinal equations of motion of the NASA-HL-20 atmospheric re-entry vehicle, a benchmark provided by Deimos Space as a representative of future re-entry vehicles, constitute the open loop model. The analysis is carried out using the optimization-based worst-case analysis tools developed at University of Leicester for Phase I of the European Space Agency (ESA) project - "Robust LPV Gain Scheduling Techniques for Space Applications" The tools make up an analysis framework using several optimization methods such as local gradient based algorithms, global evolutionary algorithms, dividing rectangles algorithm, hybrid local / global evolutionary algorithms and multi-objective algorithms. In this paper, the worst-case deviations from a predefined re-entry profile due to simultaneous variations of multiple uncertain parameters are determined by two optimization methods - hybrid differential evolution and hybrid dividing rectangles. The results demonstrate the flexibility, efficiency and reliability of the optimization-based worst-case analysis, and project it as a useful potential tool for complex controller validations in future space applications.

Item Type: Book Section
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Depositing User: Sarah Howells
Date Deposited: 19 Oct 2012 14:32
Last Modified: 21 Jul 2016 08:34
URI: http://nrl.northumbria.ac.uk/id/eprint/9832

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence