LESO-Based NMPC Tracking Control of Climbing Robot on Large Components With Variable Curvature

Ke Tan, Zeyu Gong, Bo Tao, Yuhao Zhang, Ying Shi, Zhenfeng Gu, Chong Wu, Han Ding

Abstract: Wheeled climbing robots have great application prospects in the machining of large components with variable curvature. However, its accurate motion control on variable curvature surfaces faces two fatal challenges. The varied contact states between the robot’s wheels and the variable curvature surfaces make it difficult to establish an accurate kinematics model. Additionally, there exists a different degree of robot slippage when the robot moves in different attitudes due to the dragging effect of gravity. To overcome the above problems, we first present a kinematics modeling method with instantaneous plane constraints on a variable curvature surface. Subsequently, a linear extended state observer (LESO)-based nonlinear model predictive control (NMPC) scheme is designed, in which the NMPC is used to calculate the nominal control inputs and the LESO is used to estimate and compensate for lumped disturbance brought by the robot slippage and surface constraints. Experiments on a real wind turbine blade with variable curvature show that the proposed control scheme can well eliminate the influence of lumped disturbance, and the climbing robots can achieve unbiased (AVG < 0.1 mm) and high-precision (RMSE < 2 mm) trajectory tracking. Note to Practitioners—Wheeled climbing robots, capable of adhering to curved surfaces of workpieces while in motion, provide a new approach for machining large components when equipped with machining actuators. This paper is motivated by the tracking control problem of wheeled climbing robots on curved surfaces with variable curvature, which is crucial for ensuring effective machining. The varying contact states between the wheels and the surfaces during the robot’s motion, along with the robot slippage introduced by the dragging effect of gravity, result in discrepancies between the ideal and actual motion speeds. These discrepancies introduce model uncertainties and thus pose challenges for achieving high-precision trajectory tracking. Additionally, current research on climbing robots primarily focuses on prototype development, with practitioners predominantly utilizing open-loop controller or basic model-free control schemes. This often leads to non-robust trajectory tracking of the climbing robot. To address these problems, this paper offers an accurate kinematics modeling method considering instantaneous plane constraints of the curved surfaces and a LESO-based NMPC scheme which can effectively reduce the impact of external disturbances. This approach provides a solution for automatic and high-precision trajectory tracking for climbing robot with localization system in factories, offering the potential for high-quality machining of large components.