螺旋给料流量系统单神经PID控制及仿真研究
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摘要
螺旋给料流量控制系统是一个精度要求高、易受干扰、响应滞后的复杂系统,很难建立一个精确的流量控制系统模型来对流量进行有效地控制。针对螺旋给料过程的不稳定性、响应滞后、易受干扰等问题,提出了一种单神经PID的螺旋给料流量控制方法。通过分析螺旋给料流量系统实时采集的信号,并反馈至有监督的Hebb性能学习指标的单神经元PID控制系统,通过不断学习,自动调节PID控制器的权值提高流量稳定性,并对密度变化进行了补偿。仿真实验表明,该基于单神经网络的PID方法自适应性强,稳定性高,能够有效提高系统的跟踪精度和响应速度。
The screw feeder flow control system is a complex system with high precision,susceptible interference and lag. It is difficult to establish an accurate flow control system model to control the flow effectively. Aiming at the problem of instability,response lag and susceptibility to interference in spiral feeding process,a method of spiral feed flow control for single neuron PID is proposed. By analyzing the real-time signal collected by the spiral feed flow system and feeding it back to the single neuron PID control system with supervised Hebb performance learning index,the flow stability of the PID controller is automatically adjusted by continuous learning,The change was compensated. The simulation results show that the PID method based on single neural network is easy to program,has high adaptability and high stability,and can improve the tracking precision and response speed of the system effectively.
The screw feeder flow control system is a complex system with high precision,susceptible interference and lag. It is difficult to establish an accurate flow control system model to control the flow effectively. Aiming at the problem of instability,response lag and susceptibility to interference in spiral feeding process,a method of spiral feed flow control for single neuron PID is proposed. By analyzing the real-time signal collected by the spiral feed flow system and feeding it back to the single neuron PID control system with supervised Hebb performance learning index,the flow stability of the PID controller is automatically adjusted by continuous learning,The change was compensated. The simulation results show that the PID method based on single neural network is easy to program,has high adaptability and high stability,and can improve the tracking precision and response speed of the system effectively.
引文
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[3]胡东明.液压电梯变转速闭式电液系统速度控制特性研究[D].杭州:浙江大学,2009.(Hu Dong-ming.Hydraulic elevator variable speed closed electro-hydr-aulic-system speed control characteristics[D].Hangzhou:Zhejiang Univ-ersity,2009.)
[4]贾永峰,谷立臣.模型与条件PID补偿的永磁伺服电动机驱动液压源流量控制[J].机械工程学报,2014,50(8):197-204.(Jia Yong-feng,Gu Li-chen.Model and conditional PID compensatedpermanent magnet servo motor driven hydraulic source flow control[J].China Mechanical Engineering,2012(3):286-290.)
[5]Couto R d O R.Simulator for a packing and peighing system of granul-ated powders[J].Isa Transactions,2013,52(5):672-683.
[6]彭天好,乐南更.变转速泵控马达系统转速降落补偿试验研究[J].机械工程学报,2012,48(4):175-181.(Peng Tian-hao,Yue Nan-geng.Experimental study on speed-down co-mpensation of variable speed pump-controlled motor system[J].Journalof Mechanical Engineering,2012.48(4):175-181.)
[7]时献江,王昕,王仲文.奶粉包装机动态称重智能控制系统[J].中南大学学报:自然科学版,2007,38(1).(Shi Xian-jiang,Wang-xin,Wang Zhong-wen.Automatic weighingintelligent control system for milk powder packaging machine[J].Journalof Central South University:Natural Science Edition,2007,38(1).)
[8]郑仲桥.单神经元自适应PID控制器在主动磁悬浮系统中的应用研究[J].机械设计与制造,2014(4):268-271.(Zheng Zhong-qiao.Application of single neuron adaptive PID controllerin active magnetic suspension system[J].Machinery Design&Manufa-cture,2014(4):268-271.)
[9]邱建东,欧志新.基于预测模型算法控制的动态配料系统仿真分析[J].计算机测量与控制,2010,18(9):2095-2097.(Qiu Jian-dong,Ou Zhi-xin.Simulation analysis of dynamic batchingsystem based on model algorithm control[J].Computer Measurement&Control,2010,18(9):2095-2097.)
[10]刘金琨.先进PID控制及其MATLAB仿真[M].北京:电子工业出版社,2003.(LIU Jin-kun.Advanced PID Control and MATLAB Simulation[M].Beijing:Electronic Industry Press,2003.)