Application of genetic algorithms and Taguchi methods to flight control design

Shiou Ren Liou, Ciann-Dong Yang

Research output: Contribution to journalArticle

Abstract

Genetic algorithms (GAs) are well known in most kinds of numerical methods and are widely applied in different areas of optimal studies. It is found that if the search space is wide or the fitness function that we select has high degree of nonlinear, the GA solutions could strongly depend on the setting parameters which include population size crossover rate mutation rate and the remaining size of parent in GAs. This paper applies Taguchi methods to GAs to find the best combination of the setting parameters for different flight control problems. The purpose of such a combination is to make the control more robust and close to optimal solution. To demonstrate this new idea, we consider its applications to different flight control problems for F16 fighter by using auto-stabilization LQR and H design. The simulation results not only achieve the expected optimal design for flight control problems but also justify the reliability and feasibility of the proposed method.

Original languageEnglish
Pages (from-to)223-236
Number of pages14
JournalTransactions of the Aeronautical and Astronautical Society of the Republic of China
Volume32
Issue number3
Publication statusPublished - 2000 Sep

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Taguchi methods
Genetic algorithms
Robust control
Numerical methods
Stabilization

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

Cite this

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