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Servo Electro Scale for High Precision Dynamic Weighing with Intelligent PID Controller |
YU Zhen-zhong1,ZHENG Wei-cou1,DING Liang2,LIU Xin1,HUI Jing1 |
1.Key Laboratory of Advanced Process Control for Light Industry,
Jiangnan University, Wuxi, Jiangsu 214122, China; 2.State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China |
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Abstract A dynamic and high precision weighing scale is designed for powder/granular agricultural products. The mechanical structure and the control system of the scale is desigened. The main components of the control system include S7-200 PLC, Siwarex_MS weighing model and servo motor. The servo motor, the PLC system (integrated weighing module) and the implementation mechanical structure constitutes a closed loop control system. Comparing to the open-loop control structure which mainly contain cylinder and single casting gate, it can significantly improve the accuracy of the scale. In order to overcome the nonlinear disturbance factors and the varing air materials(materials in the air with casting gate closed) which effecting on the weighing accuracy, the RBF neural network PID controller is used to the process of fine materials casting, and the adaptive correction method for the air materials was adopted. In the experiment, 25 kg rice is weighed, with an average accuracy of ±0.114% and the maxmum speed of 1100 times/h.
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[1]Zecchin P. A guide dynamic weighing for industry[J]. Measurement and Control, 2005, 38(6): 173-174.
[2]Bergeijk J V, Goense D. Dynamic weighing for accurate fertilizer application and monitoring[J]. Journal of Agricultural Engineering Research, 2001, 80(1): 25-35.
[3]陈好学. 谈影响定量包装秤包装速度的几个问题[J]. 衡器, 2004, 33(5): 38-40.
[4]温显超, 韩震宇. 定量电子包装秤中关键误差解决方案[J]. 粮食与饲料工业, 2010, (7): 9-11.
[5]张海清,李宝安,罗先和. 定量下料问题的动态称重解决方案[J]. 计量学报, 1998, 19(3): 1-5.
[6]Halimic M, Balachandran H. Performance improvement of dynamic weighing systems using linear quadratic Gaussian controller[C]// Instrumentation and Measurement Technology Conference, Vail, USA. 2003: 1537-1540.
[7]Almodarresi S. Application of artificial neural networks to intelligent weighing systems[J]. IEEE Science, Measurement and Technology, 1999, 146(6):265-269.
[8]白瑞林, 严新忠, 李军. 基于模糊神经网络技术的定量秤研究[J]. 计量学报, 2004, 25(2): 127-130.
[9]于哲峰, 杨智春. EMD技术在动态称重数据处理中的应用[J]. 机械科学与技术, 2004, 23(4): 444-446.
[10]Monfared M, Danjani A M, Abedi M. Online tuning of genetic based PID controller in LFC systems using RBF neural network and VSTLF technique[J]. Neural Network World, 2008, 18(4): 309-322.
[11]Liu Y H, Li S M. Single neuron PID control based on dynamic RBF neural network online identification[J]. Journal of System Simulation, 2006, 18(2): 804-808.
[12]Man Z H, Wu H R, Palaniswami M. An adaptive tracking controller using neural networks for a class of nolinear system[J]. IEEE Transaction on Neural Networks, 1998, 9(5): 947-955.
[13]靳红涛, 焦宗夏, 周汝胜, 等. 基于神经网络的冗余伺服系统自适应控制[J]. 机械工程学报, 2008, 44(12):249-253. |
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