Applications of genetic-Taguchi algorithm in flight control designs

Ciann Dong Yang, Chi Chung Luo, Shiu Jeng Liu, Yeong Hwa Chang

Research output: Contribution to journalReview articlepeer-review

12 Citations (Scopus)

Abstract

A genetic algorithm (GA), a well-known numerical method, is widely applied in different areas of optimal studies. It is found that if the solution-search space is wide or if the selected fitness function is highly nonlinear, the GA's solutions can strongly depend on the set parameters, which include population size, crossover rate, mutation rate, and the remaining size of the parent in the GA. This paper combines the Taguchi experimental method, which serves as a rough search tool, with the GA, which serves as a fine search tool, to find the best combination of the GA parameters for different flight-control problems. The purpose of such a combination is to make control more robust and closer to the optimal solution. To demonstrate this new idea, the writers consider its application to different flight-control problems for the F-16 fighter by using autostabilization, linear quadratic regulator (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 combination of the GA and the Taguchi method.

Original languageEnglish
Pages (from-to)232-241
Number of pages10
JournalJournal of Aerospace Engineering
Volume18
Issue number4
DOIs
Publication statusPublished - 2005 Oct 1

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Materials Science(all)
  • Aerospace Engineering
  • Mechanical Engineering

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