An adaptive evolutionary strategy and its application in the optimization of the aircraft control law in the large flight envelope

Guangwen Li, Qiuling Jia, Jingping Shi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The searching precision and the global searching ability of Evolutionary Strategy (ES) depend on the selection of the mutation step. In order to enhance the global searching ability and precision, an adaptive evolutionary strategy based on the feedback and sharing mechanism (ESBFSM) is proposed, in which the information of the current optimal searching result and sharing degree is fed into the mutating formula. By tuning the variance of the mutation operator according to the feedback information, the mutation step of ES is changed with the current searching result. And a part of individuals of the population in the later searching procedure keep higher probability of jumping out of the local minimum by the sharing mechanism. To validate the optimizing effect of the ESBFSM, the optimization of an transport aircraf's control law in the large flight envelope is done by this method, the result shows the ESBFSM is effective in optimization of the complex control system .

Original languageEnglish
Title of host publication2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009
Pages563-567
Number of pages5
DOIs
StatePublished - 2009
Event2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009 - Shanghai, China
Duration: 7 Nov 20098 Nov 2009

Publication series

Name2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009
Volume1

Conference

Conference2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009
Country/TerritoryChina
CityShanghai
Period7/11/098/11/09

Keywords

  • Aircraft
  • ES
  • Sharing mechanism

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