{"title":"Eigenstructure Assignment Based Flight Control for Advanced Fighter: An Optimization Based Approach","authors":"Yong Fan, Jihong Zhu, Chunning Yang, Zeng-qi Sun","doi":"10.1109/ICNC.2007.350","DOIUrl":null,"url":null,"abstract":"An intelligent optimization approach is proposed for eigenstructure assignment (EA) via neural network (NN) adjusting the components of output vector autonomously. The basic idea is to minimize the L2 norm of error between the desired vector and achievable vector using the designing freedom provided by EA technique. Besides, close-loop eigenvalues are also optimised within desired regions on the left-half complex plane according to the design objective to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications such as decoupling of different modes and robustness can also be easily achieved. As a demonstration, application of the proposed approach to the designing of flight control law for an advanced fighter is discussed. The simulation results show good closed loop performance and validate the proposed intelligent optimization approach of EA technique.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Natural Computation (ICNC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2007.350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
An intelligent optimization approach is proposed for eigenstructure assignment (EA) via neural network (NN) adjusting the components of output vector autonomously. The basic idea is to minimize the L2 norm of error between the desired vector and achievable vector using the designing freedom provided by EA technique. Besides, close-loop eigenvalues are also optimised within desired regions on the left-half complex plane according to the design objective to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications such as decoupling of different modes and robustness can also be easily achieved. As a demonstration, application of the proposed approach to the designing of flight control law for an advanced fighter is discussed. The simulation results show good closed loop performance and validate the proposed intelligent optimization approach of EA technique.