Human-Assisted Regulation of the Deployment of a Tethered Space Robot via Feasibility Condition Optimization and Fast Logarithmic Sliding Mode

Abstract

The feasibility analysis and performance optimization are great challenges of the underactuated deployment of a tethered space robot. This article presents an investigation into the feasibility condition optimization and stability analysis of the underactuated deployment, and proposes a feasibility-judgment-based human-assisted regulation scheme via the fast logarithmic sliding mode. The feasibility condition is generated by synthesizing a hierarchical sliding manifold, on which the in-plane angle and deployment length are synchronous, into the Lyapunov stability criterion, and optimized by a moving horizon optimization algorithm. Based on the feasibility condition, a tension control scheme is proposed to ensure that no saturated tension commands appear during the deployment. For the convenience of supervision, this article proposes a mechanism, which is derived from the desired admittance structure, to allow the human-assisted regulation to adjust the parameters of feasibility condition via a type of physical human–robot interaction. The fast logarithmic sliding mode control is proposed to stabilize the human-centric physical human–robot interaction, the operation behavior of which is estimated by neural network. The effectiveness of the proposed scheme is verified through simulations and experiments.