This paper presents the fault tolerant control (FTC) of an unmanned airship with multiple vectored thrusters in the presence of model parameter uncertainties and unknown wind disturbances. A fault tolerant control based on constrained adaptive backstepping (CAB) approach, combined with a radial basis function neural network (RBFNN) approximation, is proposed for the airship with thruster faults. A wind observer is designed to estimate the bounded wind disturbances. An adaptive fault estimator is proposed to estimate the unknown actuator faults. A weighted pseudo inverse based control allocation is incorporated to reconstruct and optimize the practical control inputs of the failed airship under constraints of actuator saturation. Rigorous stability analysis shows that trajectory tracking errors of the airship position and attitude converge to the desired set through Lyapunov theory. Numerical simulations demonstrate the fault tolerant trajectory tracking capability of the proposed NN-CAB controller under the actuator faults, even in the presence of aerodynamic coefficient uncertainties, and unknown wind disturbances.

本文提出了在存在模型参数不确定性和未知风扰的情况下，带有多个矢量推进器的无人飞艇的容错控制（FTC）。针对带有推进器故障的飞艇，提出了一种基于约束自适应反推（CAB）方法并结合径向基函数神经网络（RBFNN）逼近的容错控制方法。设计了一个风向观测器来估计有界的风扰动。提出了一种自适应故障估计器来估计未知的执行器故障。结合了基于加权伪逆的控制分配，以在致动器饱和的约束下重建和优化故障飞艇的实际控制输入。严格的稳定性分析表明，飞艇位置和姿态的轨迹跟踪误差通过李雅普诺夫理论收敛到所需的集合。数值仿真证明了所提出的NN-CAB控制器在执行器故障下的容错轨迹跟踪能力，即使在存在气动系数不确定性和未知风扰的情况下也是如此。