A quantum inspired genetic algorithm for multimodal optimization of wind disturbance alleviation flight control system

Qi BIAN, Brett NENER, Xinmin WANG

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

This paper develops a Quantum-inspired Genetic Algorithm (QGA) to find the sets of optimal parameters for the wind disturbance alleviation Flight Control System (FCS). To search the problem domain more evenly and uniformly, the lattice rule based stratification method is used to create new chromosomes. The chromosomes are coded and updated according to quantum-inspired strategies. A niching method is used to ensure every chromosome can converge to its corresponding local minimum in the optimization process. A parallel archive system is adopted to monitor the chromosomes on-line and save all potential feasible solutions in the optimization process. An adaptive search strategy is used to gradually adjust the search domain of each niche to finally approach the local minima. The solutions found by the QGA are compared with some other Multimodal Optimization (MO) algorithms and are tested on the FCS of the Boeing 747 to demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish
Pages (from-to)2480-2488
Number of pages9
JournalChinese Journal of Aeronautics
Volume32
Issue number11
Early online date14 Feb 2019
DOIs
Publication statusPublished - Nov 2019

Fingerprint

Dive into the research topics of 'A quantum inspired genetic algorithm for multimodal optimization of wind disturbance alleviation flight control system'. Together they form a unique fingerprint.

Cite this