摘要
目前,国内静重式扭矩标准机在实际应用中往往使用传统的分段式控制逻辑,会导致检定校准过程单一、缓慢。对实验室一台3 000 Nm静重式扭矩标准机进行研究后,在控制精度保持不变、保证安全与仪器使用寿命的前提下,探索更加智能的静重式扭矩标准机控制系统的控制方法,设计了一套新型基于神经网络的比例积分微分(PID)自适应控制系统软件。将反向传播(BP)神经网络算法应用于PID控制器中,对伺服平衡系统增加BP神经网络的PID控制逻辑,建立被测扭矩传感器控制系统传递函数Simulink数学模型。通过S函数编辑M文件与Simulink联系,对静重式扭矩标准机控制系统进行Simulink仿真。使用组态王建立过程控制的对象连接与嵌入(OPC)通信服务器,使可编程逻辑控制器(PLC)组态软件与Matlab进行数据交换。新的自适应整定控制算法可以有效提高静重式扭矩标准机的使用时间效率,大幅缩短扭矩标准机各级扭矩加载时间,使控制智能化、自学习化。
Currently, domestic static weight torque standard machines often use traditional segmented control logic in practice, which can lead to a single, slow calibration process. After studying a 3 000 Nm static torque standard machine in the laboratory, a new neural network-based proportional integral differential(PID) adaptive control system software is designed to explore a more intelligent control method for the control system of the static torque standard machine under the premise of keeping the control accuracy constant and ensuring the safety and instrument life. The back propagation(BP) neural network algorithm is applied to the PID controller, the PID control logic of BP neural network is added to the servo balancing system, and the Simulink mathematical model of the transfer function of the measured torque transducer control system is established. Simulink simulation of the control system of the static weight torque standard machine by S function editing M file in contact with Simulink. Use Configuration King to establish the object linking and embedding for process control(OPC) communication server for process control, so that the programmable logic controller(PLC) configuration software can exchange data with Matlab. The new adaptive adjustment control algorithm can effectively improve the efficiency of the time of use of the static weight type torque standard machine and achieve a significant reduction of torque loading time at all levels of the torque standard machine, with intelligent and self-learning control.
作者
刘健东
LIU Jiandong(Guangzhou Institute of Measurement and Testing Technology,Guangzhou 510663,China)
出处
《自动化仪表》
CAS
2022年第9期46-51,共6页
Process Automation Instrumentation
基金
广州市市场监督管理局科技基金资助项目(2020kj09)。
关键词
扭矩计量
过程控制的对象连接与嵌入通信
反向传播神经网络
静重式扭矩标准机
比例积分微分
自适应控制
Torque metering
Object linking and embedding for process control(OPC)communication
Back propagation(BP)neural network
Static weight torque standard machine
Proportional integral differential(PID)
Adaptive control
