Quaternion-based fault-tolerant control design for spacecraft attitude stabilization: an anti-saturation method

This paper investigates the problem of spacecraft attitude stabilization using an anti-saturation strategy. Taking into account the actuator faults or failures, input saturation, modeling uncertainties and external disturbances, we propose a novel adaptive neural network fault-tolerant scheme, in which a terminal sliding mode is embedded in a fault-tolerant controller (FTC) that is implemented based on radial basis function neural networks (RBFNNs). The proposed approach not only shows the ro- bustness and adaptivity with respect to unknown mass properties and external disturbances but also is capable of accommodating actuator faults or failures. Moreover, as the designed adaptive parameters are scalars, it only requires light computational load and can avoid redesign process of the controller during spacecraft operation. Finally, the feasibility of the proposed method is illustrated via a numerical example