Application of improved chaotic particle swarm optimization grey system model to thermal error modeling of machine tools

doi:10.16731/j.cnki.1671-3133.2018.06.019

Abstract

Abstract: In order to decrease the influence of thermal errors on machining precision of machine tools and to improve the prediction accuracy of Grey system Model(GM),the Improved Chaotic Particle Swarm Optimization (ICPSO) is introduced into the grey system model.One improved chaotic particle swarm optimization based grey system model is proposed to model the thermal errors of the machine tools.Firstly,the mapping of between particles of PSO and the parameters of grey system model is developed.Next,the Logistic map of chaotic theory of ICPSO initializes the location and velocity of particles.The optimal parameters and input set are obtained by optimizing search with ICPSO.Then,the model based on ICPSO-GM is established to predict the thermal errors of machine tools.The simulation shows that the thermal model of ICPSO-GM has the higher prediction precision than GM and Artificial Neural Network(ANN).The results indicate that the proposed ICPSO-GM can effectively realize the prediction of thermal errors of machine tools.

Key words: computer numercial control machines, thermal errors, chaos, Particle Swarm Optimization(PSO), Grey system Model(GM)

CLC Number:

TH161

Yu Wenli, Yao Xinhua. Application of improved chaotic particle swarm optimization grey system model to thermal error modeling of machine tools[J]. Modern Manufacturing Engineering, 2018, 453(6): 101-107.

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