Neuron Optimization Based PID Approach for Cutting Force Control

S. Jiang; Yan Shen Xu; J. Wu

doi:10.4028/www.scientific.net/KEM.315-316.85

Paper Titles

Double-CCD Stereoscopic Vision System Monitoring Chip Shape
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Machining Accuracy Enhancement by Modifying NC Program
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Dynamic Calibration of Metal Cutting Dynamometer
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Experimental Research on Technology of Ultrasonic Vibration Aided Electrical Discharge Machining (UEDM) in Gas
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Neuron Optimization Based PID Approach for Cutting Force Control
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FEA and Precision Machining on Ceramic Plunger Couple
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Friction and Wear Behaviors of Three Ceramic Composite
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Volumetric Positioning Errors of CNC Machining Tools and Laser Sequential Step Diagonal Measurement
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Sawing of Granite with Side-Slotted Diamond Segments
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Neuron Optimization Based PID Approach for Cutting Force Control

Abstract:

To improve the cutting efficiency, one of key approaches is to control with constant force in the full depth working condition. And the controller design is vital to realize the real-time feasibility and robustness of the system. A neuron optimization based PID approach is proposed in this paper and adopted in the NC cutting process. This approach optimizes the parameters of PID controller real-timely with the neural network control principle. It not only overcomes the mismatch of the open-loop system model which occurred in constant PID control, but also solves the contradiction between the calculation speed and precision in the neural network which caused by the node choosing of the hidden layer. At last, the simulation has been carried out on a NC milling machine to prove the validity and effectiveness of the proposed approach.