Entry Trajectory Generation Based on Neural Network

摘要：

A methodology for onboard generation of entry trajectory subject to all common inequality and equality constraints is developed, which makes use of the neural network as a major approach to design a complete and feasible entry trajectory instantaneously. Conventional constrained nonlinear trajectory optimization problems and control parameters generation online can be transformed into the neural network off-line training problem, given the entry initial conditions, values of constraint parameters, and final conditions. Differing with the general neural network, this approach is trained by the principles of optimal theory. The inputs of the neural network are the time-variant state variables, the outputs are the near optimal control parameters. Numerical simulations with a reusable launch vehicle model for various entry conditions are presented to demonstrate the capability and effectiveness of the approach.

关键词： entry trajectory generation neural network onboard optimization

作者: Bin Zhang Shilu Chen Min Xu

作者单位: College of Astronautics, Northwestern Polytechnical University Xian,P.R CHINA

会议类型: 国际会议

会议名称: 2011 International Conference on Electronic & Mechanical Engineering and Information Technology(EMEIT 2011)(2011年机电工程与信息技术国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 2998-3001

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）