Applications of genetic-Taguchi algorithm in flight control designs

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

研究成果: Review article同行評審

13 引文 斯高帕斯(Scopus)


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.

頁(從 - 到)232-241
期刊Journal of Aerospace Engineering
出版狀態Published - 2005 10月 1

All Science Journal Classification (ASJC) codes

  • 土木與結構工程
  • 材料科學(全部)
  • 航空工程
  • 機械工業


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