An Unmanned Helicopter Model Identification Method based on the Immune Particle Swarm Optimization Algorithm

摘要：

　　An unmanned helicopter dynamic model identification method based on immune particle swarm optimization (PSO) algorithm is approved in this paper.In order to improve the search efficiency of PSO and avoid the premature convergence,the PSO algorithm is combined with the immune algorithm.The unmanned helicopter model parameters are coded as particle,the error of flight test and math simulation model is objective function,and the dynamic model of unmanned helicopter is identified.The simulation result shows that the method has high identification precision and can realistically reflect the dynamic characteristics.

关键词： model identification immune PSO unmanned helicopter

作者: Yang Tingting Li Aijun

作者单位: College of Automation Northwestern Polytechnical University Xian,P.R.China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 2791-2793

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）