基于非线性模型预测控制的火星大气进入智能制导方法

针对火星大气进入精确制导问题,提出了基于非线性模型预测控制(nonlinear model predictive con-trol,NMPC)的智能进入制导方法.首先,考虑了进入制导约束,采用NMPC方法设计制导算法.通过引入衰减记忆滤波器,提出了基于误差信息估计的预测模型修正方法,增强系统对模型误差的鲁棒性,并利用变...

Intelligent guidance method based on nonlinear model predictive control for Mars atmospheric entry

Aiming at the precision guidance problem of the Mars atmospheric entry guidance, an intelligent guidance method based on nonlinear model predictive control (NMPC) is proposed. First, considering guidance constraints, the guidance system is designed by using the NMPC method. By introducing the fading-memory filter, the prediction model correction method based on error information estimation is proposed to enhance the robustness of the system against model errors, and the system performance is improved by using the variable prediction time domain strategy. Then the NMPC guidance system is used as the guidance template to generate the sample data set under the actual entry conditions, which conduct the off-line training of the deep neural network. Finally, in the process of entry guidance, deep neural network is used to solve control variable online quickly instead of the process of solving complex optimization problem and integral prediction, and the intelligent guidance is realized by combining with lateral guidance. The simulation results show that the proposed guidance method can calculate command quickly and realize high-precision guidance.