Fuzzy-Based Adaptive Super-Twisting Sliding-Mode Control for a Maneuverable Tethered Space Net Robot

The use of maneuverable tethered space net robot (TSNR) is a promising solution for active space debris capture and removal due to its large envelop and easy capture method. However, the flexibility and elasticity of the underactuated net present a new challenge to the control scheme. In this article, a fuzzy-based sliding-mode control is proposed and applied to the TSNR. The main contribution is that an adaptive super-twisting sliding-mode control (ASTSMC) is investigated with a novel adaption law based on a fuzzy estimator, eliminating the need for a derivative of uncertainty. The key advantage of the proposed scheme is that the passive adaption law of traditional ASTSMC is improved to an active law, and complex oscillations can be directly estimated and suppressed. The dynamics equations of the TSNR are first derived, and the control problem of the system is specified. For the unmeasurable and boundary-unknown uncertainties, the adaptive fuzzy logic scheme is employed to approximate the complex uncertainties. Stability analysis and approximation convergence of the proposed control scheme are then verified via Lyapunov stability analysis. Finally, numerical simulations on the TSNR are provided to confirm the effectiveness and robustness of the proposed scheme.