To ensure the stable flight performance and good tracking effect of the morphing aircraft in the case of sensor fault, and improve the accuracy of fault diagnosis and fault-tolerant control capability, an online active fault-tolerant control method based on belief rule base (BRB-r) expert system considering attribute reliability is proposed highly specific for the sensor fault diagnosis and fault-tolerant control of the morphing aircraft. Firstly, the aerodynamic parameter model and longitudinal nonlinear dynamic model of morphing aircraft are presented. Considering the external disturbance and sensor fault, the switched linear parameter varying (LPV) fault model of morphing aircraft is established by using the least fitting method and Jacobian linearization method. Then, based on BRB-r expert system, a sensor fault diagnosis and fault-tolerant control model of morphing aircraft is constructed. The reliability of sensor monitoring index is analyzed by statistical method, and evidence reasoning (ER) algorithm is introduced to improve the accuracy of fault diagnosis and fault-tolerant control effect. Finally, the projection operator covariance matrix adaptive optimization strategy (P-CMA-ES) algorithm is used to optimize the fault diagnosis and fault tolerant control model, which reduces the complexity of the system and improves the efficiency of fault diagnosis. The simulation results show that the sensor fault diagnosis accuracy of the morphing aircraft can reach 98.75%. When the sensor fault degree is less than 50%, the proposed method can effectively overcome the sensor fault and external disturbance, ensuring the stable flight of the morphing aircraft, and exhibiting strong fault-tolerant control capability and robust performance.