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 article

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

Fingerprint

Genetic algorithms
Taguchi methods
Robust control
Numerical methods

All Science Journal Classification (ASJC) codes

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

Cite this

Yang, Ciann-Dong ; Luo, Chi Chung ; Liu, Shiu Jeng ; Chang, Yeong Hwa. / Applications of genetic-Taguchi algorithm in flight control designs. In: Journal of Aerospace Engineering. 2005 ; Vol. 18, No. 4. pp. 232-241.
@article{a0d0836d5b7a4aaa88e1cc5159bbed46,
title = "Applications of genetic-Taguchi algorithm in flight control designs",
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.",
author = "Ciann-Dong Yang and Luo, {Chi Chung} and Liu, {Shiu Jeng} and Chang, {Yeong Hwa}",
year = "2005",
month = "10",
day = "1",
doi = "10.1061/(ASCE)0893-1321(2005)18:4(232)",
language = "English",
volume = "18",
pages = "232--241",
journal = "Journal of Aerospace Engineering",
issn = "0893-1321",
publisher = "American Society of Civil Engineers (ASCE)",
number = "4",

}

Applications of genetic-Taguchi algorithm in flight control designs. / Yang, Ciann-Dong; Luo, Chi Chung; Liu, Shiu Jeng; Chang, Yeong Hwa.

In: Journal of Aerospace Engineering, Vol. 18, No. 4, 01.10.2005, p. 232-241.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Applications of genetic-Taguchi algorithm in flight control designs

AU - Yang, Ciann-Dong

AU - Luo, Chi Chung

AU - Liu, Shiu Jeng

AU - Chang, Yeong Hwa

PY - 2005/10/1

Y1 - 2005/10/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=26644453717&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=26644453717&partnerID=8YFLogxK

U2 - 10.1061/(ASCE)0893-1321(2005)18:4(232)

DO - 10.1061/(ASCE)0893-1321(2005)18:4(232)

M3 - Review article

AN - SCOPUS:26644453717

VL - 18

SP - 232

EP - 241

JO - Journal of Aerospace Engineering

JF - Journal of Aerospace Engineering

SN - 0893-1321

IS - 4

ER -