Skip to main navigation Skip to search Skip to main content

Solution of steady state of aircraft based on mixture genetic algorithm

  • Zhi Bo Luan*
  • , Shu Tao Zheng
  • , Hong Ren Li
  • *Corresponding author for this work
  • School of Mechatronics Engineering, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

To obtain the accurate solutions of the steady state of aircraft, a hybrid genetic algorithm was proposed according to the analysis of the basic characteristics and constraints of the steady state. Based on the concept of "individual learning potentiality", this algorithm logistically integrates the Lamarckian learning and Baldwinian learning mechanisms. It rationally distributes the number of local search among the population to make the advantage of the learning into full play, meanwhile inhibit its disadvantage. The algorithm can solve any preassigned steady state on the basis of the state variables rather than the real form of the aerodynamic model. Simulation results validate the proposed algorithm that combines the two learning mechanisms.

Original languageEnglish
Pages (from-to)165-170
Number of pages6
JournalJilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
Volume41
Issue number1
StatePublished - Jan 2011
Externally publishedYes

Keywords

  • Artificial intelligence
  • Baldwinina learning
  • Genetic algorithm
  • Individual learning potentiality
  • Lamarckian learning
  • Steady flight state

Fingerprint

Dive into the research topics of 'Solution of steady state of aircraft based on mixture genetic algorithm'. Together they form a unique fingerprint.

Cite this