Optimized Adaptive Impedance Control Based on Robotic Seven-Axis Linkage Grinding Platform

Yilin Mu, Ziling Wang, Size Liang, Lai Zou

Abstract: In order to achieve control of the seventh axis during the robotic belt grinding, the adaptive impedance control algorithm has been proposed. By comparing the steady-state error of adaptive impedance controller (AIC) and impedance controller (IC) from simple step signals, slope signals, to complex trigonometric function signals, the performance of controller is analyzed. The Simulink simulation model of AIC is constructed, through simulation analysis, the impact of key parameters ϕ and bd in the AIC on controller performance is obtained, and the two parameters are optimized through the improved cat swarm optimization (ICSO) algorithm. During the optimization process, the two mutually constrained optimization objectives of minimum contact force tracking error and shortest response time are constructed into the final objective function through weight coefficient variation method, ultimately achieving the improvement of controller performance. The optimized controller is transformed from continuous domain to discrete domain through backward difference dispersion method, ultimately achieving the control of seventh axis.