A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft

Qi Bian, Brett Nener, Xinmin Wang

Research output: Contribution to journalArticle

Abstract

Coordinated aileron and rudder control is crucial to the lateral control stability augmentation of an aircraft. In this paper, a modified non-dominated sorting genetic algorithm II is proposed to not only optimize the control allocation between the aileron and rudder channels on different flying quality levels but also explore the relationships between the optimum solutions and the state variables of the aircraft. In doing so, a digital, nets-based stratification method is used to initialize the search chromosomes more evenly. To improve the search efficiency of the algorithm, crowding-distance-based interpolation and elimination strategies are developed to approach the optimum Pareto frontier as close as possible. Moreover, a dynamic depth search method is proposed to balance between the global and local explorations. Finally, the control allocation relationships between the aileron and rudder channels on different flying quality levels are illustrated. The comparative simulations on a six-degree-of-freedom Boeing 747 model are carried out to verify the feasibility of the proposed algorithm.

Original languageEnglish
Pages (from-to)17696-17704
Number of pages9
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Cite this

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title = "A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft",
abstract = "Coordinated aileron and rudder control is crucial to the lateral control stability augmentation of an aircraft. In this paper, a modified non-dominated sorting genetic algorithm II is proposed to not only optimize the control allocation between the aileron and rudder channels on different flying quality levels but also explore the relationships between the optimum solutions and the state variables of the aircraft. In doing so, a digital, nets-based stratification method is used to initialize the search chromosomes more evenly. To improve the search efficiency of the algorithm, crowding-distance-based interpolation and elimination strategies are developed to approach the optimum Pareto frontier as close as possible. Moreover, a dynamic depth search method is proposed to balance between the global and local explorations. Finally, the control allocation relationships between the aileron and rudder channels on different flying quality levels are illustrated. The comparative simulations on a six-degree-of-freedom Boeing 747 model are carried out to verify the feasibility of the proposed algorithm.",
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A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft. / Bian, Qi; Nener, Brett; Wang, Xinmin.

In: IEEE Access, Vol. 7, 2019, p. 17696-17704.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft

AU - Bian, Qi

AU - Nener, Brett

AU - Wang, Xinmin

PY - 2019

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AB - Coordinated aileron and rudder control is crucial to the lateral control stability augmentation of an aircraft. In this paper, a modified non-dominated sorting genetic algorithm II is proposed to not only optimize the control allocation between the aileron and rudder channels on different flying quality levels but also explore the relationships between the optimum solutions and the state variables of the aircraft. In doing so, a digital, nets-based stratification method is used to initialize the search chromosomes more evenly. To improve the search efficiency of the algorithm, crowding-distance-based interpolation and elimination strategies are developed to approach the optimum Pareto frontier as close as possible. Moreover, a dynamic depth search method is proposed to balance between the global and local explorations. Finally, the control allocation relationships between the aileron and rudder channels on different flying quality levels are illustrated. The comparative simulations on a six-degree-of-freedom Boeing 747 model are carried out to verify the feasibility of the proposed algorithm.

KW - MNSGA-II

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KW - flight control system

KW - PARTICLE SWARM OPTIMIZATION

KW - GENETIC ALGORITHM

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