关键词: 可重复使用运载器, 未知扰动, 执行器部分失效, 增量反步控制, 神经网络逼近, 鲁棒容错控制

Abstract: Aiming at the attitude control problem of reusable launch vehicle in complex reentry environment, considering the unknown disturbance of atmosphere, the uncertainty of aerodynamic parameter modeling and the possible local faults of actuator, the controllers of attitude angle loop and angular velocity loop are designed based on incremental backstepping and RBF neural network. Because the neural network has good unknown approximation ability, RBFNN is used to estimate the high-order term of Taylor expansion and the influence of the above unknown disturbances in the IBS design process, and compensate them in the control law. The simulation results show that the designed control system can effectively improve the tracking accuracy of in-structions under the influence of unknown disturbances, and has less dependence on the modeling of aircraft information, so it has good robust fault tolerance.

Key words: reusable launch vehicle, unknown disturbance, partial failure of actuator, incremental backstepping, neural network approxima-tion, robust fault tolerant control