Mechanical arm error compensation method based on improved RBF neural network
The invention belongs to the technical field of mechanical arm precision control, and relates to a mechanical arm error compensation method based on an improved RBF neural network, which mainly comprises two parts of geometric error identification based on a preprocessing sequence quadratic programm...
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creator | WANG JIN FANG ZIYANG LU GUODONG ZHU JUNJIE ZHENG WENXIN LI XIAOFEI ZHANG HAIYUN |
description | The invention belongs to the technical field of mechanical arm precision control, and relates to a mechanical arm error compensation method based on an improved RBF neural network, which mainly comprises two parts of geometric error identification based on a preprocessing sequence quadratic programming algorithm and non-geometric error identification based on a particle swarm optimization RBF neural network. In a geometric error identification compensation stage, a mechanical arm high-dimensional solution space is reduced to a non-convex low-dimensional subspace through preprocessing, and then sequential quadratic programming is designed to solve geometric compensation data; in a non-geometric error identification compensation stage, designing an RBF neural network algorithm based on particle swarm optimization to adaptively predict non-geometric error compensation data; and the positioning error of the mechanical arm is comprehensively compensated by combining geometric and non-geometric error compensation d |
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subjects | CHAMBERS PROVIDED WITH MANIPULATION DEVICES HAND TOOLS MANIPULATORS PERFORMING OPERATIONS PORTABLE POWER-DRIVEN TOOLS TRANSPORTING |
title | Mechanical arm error compensation method based on improved RBF neural network |
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