Force control approaches research for robotic machining based on particle swarm optimization and adaptive iteration algorithms

Abstract

Purpose The purpose of this paper is to reduce the strain and vibration during robotic machining. Design/methodology/approach An intelligent approach based on particle swarm optimization (PSO) and adaptive iteration algorithms is proposed to optimize the PD control parameters in accordance with robotic machining state. Findings The proposed intelligent approach can significantly reduce robotic machining strain and vibration. Originality value The relationship between robotic machining parameters is studied and the dynamics model of robotic machining is established. In view of the complexity of robotic machining process, the PSO and adaptive iteration algorithms are used to optimize the PD control parameters in accordance with robotic machining state. The PSO is used to optimize the PD control parameters during stable-machining state, and the adaptive iteration algorithm is used to optimize the PD control parameters during cut-into state.