基于递归神经网络的再入飞行器最优姿态控制

针对再入飞行器的姿态跟踪问题,基于递归神经网络提出最优跟踪控制.采用反步法和递归神经网络,设计自适应前馈控制,将再入飞行器的最优姿态跟踪问题转化为等价的姿态角误差/角速率误差最优调节问题.采用自适应动态规划技术,解决最优调节问题.引入神经网络估计最优控制中的代价函数,推导最优反馈控制律,同时保证Hamilton–Jac...

Recurrent neural network-based optimal attitude control of reentry vehicle

An optimal control is proposed based on recurrent neural networks (RNNs) for the attitude tracking problem of reentry vehicle. Firstly, backstepping and RNNs are introduced to accomplish the adaptive feedforward control. The optimal attitude tracking problem of the reentry vehicle is transformed into the equivalent optimal regulation problem for attitude angle error/angular rate error. Then, adaptive dynamic programming is adopted to fulfill the optimal regulation problem. The neural network is utilized to estimate the cost function in the optimal control, subsequently the optimal feedback control law is constructed, and the estimation error in HJI equation is minimized. The stability analysis based on Lyapunov theory can ensure that all the signals in the closed-loop system, especially attitude angle error, are uniformly ultimately bounded. The effectiveness of the proposed control strategy is verified by numerical simulation in MATLAB/Simulink environment.mulation in MATLAB/SIMULINK environment.