MPC implementation in a PLC based on Nesterov's fast gradient method

M. Pereira, D. Limón, D. M. D. L. Peña, T. Alamo
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引用次数: 6

Abstract

This work presents a linear quadratic model predictive controller (MPC) implemented in an industrial programable logic controller (PLC). The control law is calculated by solving on-line the quadratic programming problem derived from the optimization control problem of MPC. Nesterov's fast gradient algorithm has been used to solve the corresponding linear quadratic MPC problems with input constraints. The predictive controller has been implemented in a Schneider Electric M340 using the standard structured language from the IEC 1131.1 norm. The memory and computational time requirements of the proposed implementation have been characterized through extensive simulations. In addition, the properties of the proposed controller have been experimentally demonstrated using a test-bed in which the MPC running in the M340 controls a model of a quadruple-tank process simulated in Matlab/Simulink through an OPC server.
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基于Nesterov快速梯度法的MPC在PLC中的实现
本文提出了一种在工业可编程逻辑控制器(PLC)中实现的线性二次模型预测控制器(MPC)。通过在线求解由MPC优化控制问题导出的二次规划问题来计算控制律。Nesterov的快速梯度算法已被用于求解相应的具有输入约束的线性二次型MPC问题。该预测控制器已在施耐德电气M340中使用来自IEC 1131.1规范的标准结构化语言实现。所提出的实现的内存和计算时间需求已经通过广泛的模拟进行了表征。此外,所提出的控制器的特性已经通过实验验证,在M340中运行的MPC控制通过OPC服务器在Matlab/Simulink中模拟的四缸过程模型。
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