An improved NSGA-II based control allocation optimisation for aircraft longitudinal automatic landing system

Qi Bian, Brett Nener, Xinmin Wang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, an Improved Nondominated Sorting Genetic Algorithm II is proposed for control allocation optimisation in the field of aircraft automatic landing. The initial chromosomes are generated by using a quasi-random sequence to get a better initial searching ability. The adaptive crossover operator and mutation operator are proposed for the dynamic searching area by adaptively relocating the target according to the current searching results. The corresponding online boundary adjustment strategy is created to maintain the robustness of the algorithm during the whole searching process. The control relationships between the elevator and engine channels are presented and a set of feasible solutions are chosen as a reasonable control range for the ALS design. Finally, a 6 Degrees of Freedom (6DoF) rigid model of the F/A-18 with external wind perturbation is used as a test bed to demonstrate the feasibility of the proposed method.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalInternational Journal of Control
Early online date7 May 2018
DOIs
Publication statusPublished - 24 May 2018

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