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Simulation Study on Civil Aviation Human Reliability Learning from Incidents Using System Dynamics Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Control Parameter Optimization for a Longitudinal Automatic Landing System via a Multi-objective Genetic Algorithm

Authors : Cheng Chen, Jie Ke, Haonan Xu, Bei Lu, Qifu Li

Published in: Proceedings of the International Conference on Aerospace System Science and Engineering 2021

Publisher: Springer Nature Singapore

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Abstract

It is challenging for control design and parameter optimization of a civil aircraft automatic landing system due to the complex application environment and high tracking precision requirement. In this paper, a parameter optimization method based on the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to reduce the workload of control gain tuning and improve the performance of the autoland system. To facilitate the eventual engineering application, the flying quality indices are explicitly considered when defining the objective function for optimization. The proposed method is applied to design a longitudinal automatic landing system. It greatly simplifies the design process, and simulation results also demonstrate the effectiveness of the method.

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Metadata
Title
Control Parameter Optimization for a Longitudinal Automatic Landing System via a Multi-objective Genetic Algorithm
Authors
Cheng Chen
Jie Ke
Haonan Xu
Bei Lu
Qifu Li
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of the International Conference on Aerospace System Science and Engineering 2021

Print ISBN: 978-981-16-8153-0

Electronic ISBN: 978-981-16-8154-7

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-16-8154-7_10

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