The dual-body tethered satellite system, which consists of two spacecraft connected by a single tether, is one of the most promising configurations in numerous space missions. To ensure the stability of deployment, the radial basis function neural network-based adaptive terminal sliding mode controller is proposed for the dual-body tethered satellite system with the model uncertainty and external disturbance. The terminal sliding mode controller serves as the main control framework for its properties of the strong robustness and finite-time convergence. The radial basis function neural network is adopted to approximate the model uncertainty, in which the weight vector of the radial basis function neural networks and the unknown upper bound of the external disturbance are estimated by using two adaptive laws. Finally, the Lyapunov theory and numerical simulations are used to prove the validity of the proposed controller.
Tethered satellite formation has obtained widespread attention in recent years. The main causes of the increasing study interest around tethered formation lie in its promised applications in space, such as interferometric measurements. The deployment of a tethered formation system in low Earth orbit is investigated in this paper. The orbital tethered system consists of three nanosatellites connected via tethers end-to-end, and the desired arrangement for the end masses is an equilateral triangle. For the sake of brevity, the formation system is modeled as a particle-rigid rod system, in which the elasticity of the tethers is omitted. The deployment process is carried out using tension forces and active external forces generated by low-thrust engines. The numerical results confirm that it is possible to deploy a triangular tethered system, which rotates at a given initial angular velocity, to an expected arrangement using the proposed control law of tether tensions and active forces.
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