Region-Based Force Control Strategy for Improving Profile Accuracy of Blade on 7-Axis Linkage Robotic Grinding System

Nonlinear time-varying contact state and uneven allowance distribution are factors to prevent traditional robotic belt grinding from high-precision machining of aero-blade. For this case, a novel region-based force control (RFC) strategy with consideration of regional division is proposed to achieve high-precision grinding. Ideal normal grinding force at cutter-contact (CC) points is calculated based on allowance distribution and principle curvature of the corresponding CC points. Then, CC points with similar ideal normal grinding force are divided into one region based on the iterated force threshold. Furthermore, an adaptive impedance controller based on online neural network (AIC-ONN) is designed to enhance force control accuracy. The related verification experiment results indicate that the control accuracy with AIC-ONN has increased by 78.43% than that with proportion integration differentiation (PID). Furthermore, the grinding experiment of blade is developed on the seven-axis linkage robotic grinding system. The profile accuracy value with RFC of whole profile is 0.395 mm. The results indicate that profile accuracy with RFC have improved by 57.06% and 45.14% than that with conventional grinding (CG) and constant force grinding (CFG), respectively.

Automated summary

This paper proposes a novel region-based force control strategy for achieving high-precision grinding. By considering regional division and calculating ideal grinding force, the traditional robotic belt grinding method is improved. An adaptive impedance controller is also designed to enhance force control accuracy. Experimental results demonstrate the effectiveness and advantages of this approach.