Information-optimization based neural network of force control in cutting process

ZHANG Yi
（Department of Mechanical & Electrical Engineering， Guangdong Communication Polytechnic，
Guangzhou 510800， China）

Abstract： In order to improve productivity and ensure precision of machining process，information principle and neural network were applied in control of machining process with the constant force control as study object. The neural network was used as information-transmission channel for inputs and outputs of machining process control with information entropy as unified performance indexes at various levels of the intelligent control system. The objective function of neural network based on information-optimization was confirmed and learning algorithm of the three-layer BP neural network was derived. The information-optimization based neural network control system of constant force in machining process was proposed. Simulation instance of machining process proves that，compared with self-adaptive neural network control，the proposed control is of faster and more accurate convergence，less vibration and less overshoot，and behaves with better comprehensive properties. The research result provides effective way for information theory to be applied in control process of machining.
Key words： machining process； information entropy； neural network； intelligent control