一种面向空天飞机再入的智能自适应复合控制方法

针对空天飞机再入横、侧向通道的姿态控制问题，设计了一种智能神经网络自适应复合控制方法，基于误差反馈学习准则在线更新神经网络权重以补偿全量姿态控制律输出的姿态控制指令。同时，面向再入过程横侧通道的强耦合问题，引入了耦合控制系数，以降低横、侧通道间的控制干扰。此外，提出了一种自适应链式控制分配律，在控制信号中引入正交优化多正弦激励，基于递推最小二乘方法对气动参数进行在线辨识，进而实时更新链式分配策略。最后，对空天飞机再入横侧向通道的神经网络自适应复合控制方法进行数学仿真校验，验证了该方法的有效性和鲁棒性。

An Intelligent Adaptive Compound Control Method for Aerospace Plane Reentry

In view of the attitude control problem of the reentry roll and yaw channels of the aerospace plane, an intelligent neural network adaptive compound control method is designed. Based on error feedback learning criterion, the neural network weights are updated online to compensate the attitude control instructions output by the total attitude control law. At the same time, for the strong coupling problem in reentry process, the coupling control coefficient is introduced to reduce the control interference between the roll and yaw channels. In addition, an adaptive chain control allocation law is proposed. The orthogonal optimization multi sine excitation is introduced into the control signal, and the aerodynamic parameters are identified online based on the recursive least squares method, and then the chain allocation strategy is updated in real time. Finally, the effectiveness and robustness of the neural network adaptive compound control method for the reentry roll and yaw channels of the aerospace plane are verified by the mathematical simulation.