Research on slip state identification and energy optimization control of four-split transmission line de-icing robot

Transmission line de-icing robots are intelligent devices designed for ice removal operations on transmission lines. However, when operating on complex iced line, especially during uphill and downhill processes, the four wheels of the robot are prone to slipping which not only reduces de-icing efficiency and wastes energy but also severely restricts the completion of the operation. To address this issue, this paper focuses on the stable climbing and energy optimization of de-icing robots on iced conductors. Firstly, based on the catenary theory, we formulate the geometric state equation for the four-split iced transmission line. To quantitatively analyze the influence of slope change on the normal load distribution of the front and rear walking wheels, a rigid body static model of the robot including geometric size characteristics is established. The analytical formula of the minimum theoretical pressing force required for the front and rear wheels to maintain stable climbing is derived. It is theoretically demonstrated that the implementation of differential pressing force distribution can effectively suppress slipping. In addition, leveraging the robot’s unique configuration of active walking and driven pressing, a real-time slip rate monitoring model based on the speed difference between the driving wheel and pressing wheel is established. In response to the uncertainty of the icing conditions and the non-linearity of the pressing mechanism, a dual closed-loop fuzzy adaptive control system is designed. With the objectives of front-wheel anti-slip compensation and rear-wheel energy saving, the proposed system realizes slip suppression and energy optimization. Finally, the feasibility and effectiveness of the proposed method are evaluated through numerical simulations and prototype experiments.