Finite Horizon Worst Case Analysis of Linear Time-Varying Systems Applied to Launch Vehicle

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

This article presents an efficient approach to compute the worst case gain of the interconnection of a finite time horizon linear time-varying system and a perturbation. The input/output behavior of the uncertainty is described by integral quadratic constraints (IQCs). A condition for the worst case gain of such an interconnection can be formulated using dissipation theory as a parameterized Riccati differential equation, which depends on the chosen IQC multiplier. A nonlinear optimization problem is formulated to minimize the upper bound of the worst case gains over a set of admissible IQC multipliers. This problem can be efficiently solved with a custom-tailored logarithmically scaled, adaptive differential evolution algorithm. It provides a fast alternative to similar approaches based on solving semidefinite programs. The algorithm is applied to the worst case aerodynamic load analysis of an expendable launch vehicle (ELV). The worst case load of the uncertain ELV is calculated under wind turbulence during the atmospheric ascend and compared to results from nonlinear simulation.

Details

Original languageEnglish
Article number10091683
Pages (from-to)2393-2404
Number of pages12
JournalIEEE transactions on control systems technology
Volume31
Issue number6
Publication statusPublished - 3 Apr 2023
Peer-reviewedYes

External IDs

WOS 000967961900001
Scopus 85153333858
ORCID /0000-0001-6734-704X/work/142235783
ORCID /0000-0002-0016-9637/work/145224592
dblp journals/tcst/BiertumpfelPBP23
Mendeley 96a6901b-d70c-3279-b46d-b2cc9b226caa

Keywords

DFG Classification of Subject Areas according to Review Boards

Keywords

  • Flight control, Frequency-domain analysis, Perturbation methods, Robustness, Time-domain analysis, Time-varying systems, Uncertainty, Upper bound, integral quadratic constraints (IQCs), metaheuristics, robust control, time-varying systems, Metaheuristics, Robust control