文摘
In current study for wing flutter of reentry vehicle, the effect of input saturation to wing flutter is rarely considered and few of the fault-tolerant control problem is taken into account. In this paper, we use the radial basis function neural network and the finite-time adaptive fault-tolerant control technique to deal with the wing flutter problem, which is subject to input saturation, parameter uncertainties and external disturbances. Sensor and actuator faults are both considered in the control design. Firstly, an optimal flight trajectory of reentry vehicle is designed using the conjugate gradient method, so as to decrease the aerodynamic heating rate and temperature on the surface of the reentry vehicle. Then based on the trajectory optimization, we ignore the effect of temperature, and build up the motion equation of wing flutter. Finally, a finite-time H∞ adaptive fault-tolerant controller is introduced. Simulation results indicate that, the optimized trajectory designed may decrease the aerodynamic heating rate of the reentry vehicle; the designed fault-tolerant controller can effectively deal with the faults in the system and can promptly suppress the wing flutter as well.