Neuro-adaptive Sliding Mode Fault-tolerant Control of Hypersonic Vehicle under Actuator Fault

This paper proposed a neuro-adaptive sliding mode fault-tolerant control (NASMFTC) method for the problem of actuator control gain loss fault in hypersonic vehicles. Described as the elevator yaw angle and the engine throttle setting valve fault. The controller combines the robust adaptive algorithm with the radial basis function (RBF) based neural network (NN) method for the hypersonic vehicle longitudinal motion model. The proposed fault-tolerant control method has the following advantages: 1. No need to estimate the value of the actuator fault; 2. The designed control algorithm is simple in structure and does not require a large amount of online calculation, can quickly deal with the occurrence of faults; 3. Can ensure that the system still has the ability to stably track in the case of constant or time-varying actuator faults. The final simulation experiment verifies the effectiveness of the proposed method.