A novel dynamic observer-based contact force control strategy in robotic grinding to improve blade profile accuracy

Abstract

Complex curvature changes and uneven allowance distribution significantly hinder the ability of traditional robotic belt grinding methods to achieve high-precision blade processing. To resolve this problem, a novel dynamic observer-based contact force control strategy is proposed in this paper by considering the dynamic contact force (DCF) model and partitioned force control (PFC) strategy. The DCF model is developed by considering the contact pressure distribution across different blade areas, while the over-grinding depth error is derived by analyzing the contact pressure coupling influenced by row spacing. The CC points with large allowance are divided into regions based on the variation of ideal normal contact force. Then, the reference normal contact force for each region is determined. Moreover, a dynamic observer-based adaptive impedance controller (DO-AIC) is developed to enhance reference normal contact force control. Verification experiment showed that DO-AIC increased force control accuracy by 78.27% compared to without the controller. Furthermore, four sets of robotic grinding experiments on turbine blades were performed to validate the superiority of the proposed method. The results showed that with DO-PFG, the surface profile accuracy at blade four areas improved to 0.244 mm, 0.188 mm, 0.193 mm, and 0.203 mm, representing improvements of 53.7%, 79.57%, 59.37%, and 67.26% compared to TG, respectively.