Transactions of Materials and Heat Treatment

Title：Improvement of hydraulic control system based on BP neural network PID control

Authors： Ni Hongqi Wang Shuaijun Wang Shuqiang Wang Jianbin Wang Fengshuang

Unit： Shenyang University of Chemical Technology Qinhuangdao North Metal Hose Co. Ltd.

KeyWords： closed press hydraulic servo system BP neural network PID contorller

ClassificationCode：TP273

year,vol(issue):pagenumber：2015,40(11):67-70

Abstract：

The slider of closed press needs precise control of displacement when contacted with the workpiece, based on the characteristics of the large inertia, time-varying, high nonlinera and differenty in obtaining relative precise mathematical model of hydraulic servo system for closed press, the ideal effect can not be achieved easily by traditional PID controller. Combined BP network with traditional PID controller, the optimal combination of parameters and more precise slider displacement control were realized by the real-time detection of sliders actual value, set value and error value at different time with the help of the on-line self-learning ability of neural network to adjust the PID parameters KP、KI、KD，online. The control performance of BP network is superior to traditional PID controller. The curve obtained by simulation comparison analysis shows that PID controller of BP neural network can effectively improve the hydraulic servo control system.

Funds：

辽宁省教育厅科学技术研究项目（L2013170）

倪洪启（1967-），男，博士，副教授王帅军（1988-），男，硕士研究生

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