LAUSR

Gyrowheel is an innovative instrument that can function as a momentum actuator and simultaneously measure angular rates for small spacecrafts. Unlike traditional gyroscopes, the gyrowheel dynamics is significantly complicated and nonlinear, subject to various uncertainties and disturbances. This results in challenges to realize accurate angular rate sensing with the gyrowheel. To overcome the drawbacks of the existing methods, the external angular rate sensing problem is investigated in this paper. A radial basis function neural network is adopted and further combined with an augmented observer to deal with the nonlinearities, uncertainties and disturbances of the gyrowheel system. Employing the neuro-augmented observer, this paper proposes a practical angular rate sensing approach with satisfactory accuracy and without the requirement of an exact knowledge of the gyrowheel dynamics. Simulation tests illustrate the effectiveness and superiority of the proposed method.