TY - JOUR
T1 - An improved NSGA-II based control allocation optimisation for aircraft longitudinal automatic landing system
AU - Bian, Qi
AU - Nener, Brett
AU - Wang, Xinmin
PY - 2018/5/24
Y1 - 2018/5/24
N2 - 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.
AB - 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.
KW - Aircraft automatic landing
KW - control allocation optimisation
KW - multi-objective genetic algorithm
UR - http://www.scopus.com/inward/record.url?scp=85047308550&partnerID=8YFLogxK
U2 - 10.1080/00207179.2018.1473643
DO - 10.1080/00207179.2018.1473643
M3 - Article
AN - SCOPUS:85047308550
SP - 1
EP - 12
JO - International Journal of Control
JF - International Journal of Control
SN - 0020-7179
ER -