An improved Optimal Guidance Law with impact angle constraints based on Genetic Algorithms

摘要：

In this paper,an improved formulation of optimal guidance law based on genetic algorithms is proposed.Linear quadratic optimal control theory is derived to consider terminal velocity maximization,also genetic algorithms are employed to search weight coefficient matrix of the linear quadratic performance index optimum process problem.In the genetic algorithms,a combination of the Roulette Wheel and Elitism methods is adopted,and penalty function is added to performance index.Consequently,terminal position accuracy and impact angle constraints are satisfied.Numerical simulation results illustrate that the proposed optimal guidance law based on genetic algorithms show better performance compared with conventional method and is rather robust.

关键词： optimal guidance law impact angle constraints linear quadratic control genetic algorithms.

作者: Zongzhun Zheng Yongji Wang Hao Wu

作者单位: Department of Control Science and Engineering,Key Laboratory of Ministry of Education for Image Processing and Intelligent Control,Huazhong University of Science and Technology,Wuhan,Hubei Province,430074,China

会议类型: 国际会议

会议名称: International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)

会议地点: 上海

会议语种:英文

在线出版日期: 2008-06-29（万方平台首次上网日期，不代表论文的发表时间）