Fractional-order deployment control of space tethered satellite via adaptive super-twisting sliding mode

This paper proposes a novel adaptive super-twisting sliding mode control scheme with the fractional-order terminal attractor, realizing a fast and stable deployment of space tethered satellite (STS). The considered STS system takes both in-plane and out-of-plane motions into account, whose nonlinear dynamics and open-loop error dynamics are derived. The proposed scheme investigates a super-twisting sliding mode controller with the fractional-order terminal attractor, and an adaptive law based on the RBF neural network (RBFNN) estimator. Significantly, the former accelerates the convergence speed of system states and smooths the control effect. The latter handles the adverse effect of system uncertainty and external disturbance, receiving a more stable deployment performance. According to the presented Lyapunov-based approach, the adaptive gains of the proposed controller are derived to adjust the control effect adaptively under the practical situation, and the finite convergence time is estimated to verify the finite-time stability. Finally, simulation results on the tether deployment of STS are provided to validate the effectiveness and superiority of the proposed controller.