摘要
针对月球软着陆过程中的控制问题 ,提出了一种将最优理论和非线性神经元控制相结合的控制制导方案。其主要内容是 ,根据终端着陆条件和性能指标 ,以由庞氏极大值原理得出从近月点到月面的最优着陆轨迹为基础 ,给出一种基于人工神经元网络的非线性最优控制策略 ,使被控系统能通过神经网络对非线性的映射能力实现某种最优的非线性控制。
Returning to Moon has become a top topic recently.Many studies have shown that soft landing is a challenging problem in lunar exploration.The lunar soft landing in this paper begins from a 100km circular lunar parking orbit .Once the landing area has been selected and it is time to deorbit for landing,a ΔV burn of 19\^4m/s is performed to establish an 100×15km elliptical orbit.At perilune,the landing jets are ignited,and a propulsive landing is performed.A guidance and control scheme for lunar soft landing is proposed in this paper,which combines optimal theory with nonlinear neuro\|control.Basically,an optimal nonlinear control law based on an artificial neural network is presented,on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index.Therefore some optimal nonlinear control law can be carried out in the soft landing system due to the nonlnear mapping function of the neural network.The feasibility and validity of the control law are verified in a simulation experiment.
出处
《系统工程与电子技术》
EI
CSCD
1999年第12期31-36,共6页
Systems Engineering and Electronics
基金
国家自然科学基金资助项目!( 19782 0 0 4)
关键词
软着陆
最优制导控制
月球探测
神经元
Lunar Soft Landing\ \ Neuro\|Control\ \ Nonlinear System\ \ Optimum Trajectory
