神经网络纠错广义预测控制在网络控制系统中的应用

Aiguo Wu, Dongqing Wang, Jin Liang
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引用次数: 11

摘要

针对网络控制系统不确定时延的特点,介绍了两种控制方案。为了克服建模误差和系统不确定性的影响,提出了在网络控制系统中应用广义预测控制(GPC)的思想,进一步基于BP神经网络建立误差预测模型,并用误差预测值补偿输出预测值,形成了一种新的GPC控制算法。构建了基于以太网的网络化控制系统,测试了数据传输的随机时延特性。在系统中比较了PID、GPC和带纠错的GPC三种控制方法。结果表明,带纠错的GPC方法是三种方法中性能最好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of generalized predictive control with neural network error correction in networked control system
With regards to the characteristics of uncertain delay of networked control system, two control schemes are introduced. To overcome the influence of modeling error and uncertainty of a system, an idea of using generalized predictive control (GPC) is proposed in the networked control system, an error predictive model is further built based on BP neural network, and error predictive value is used to compensate output predictive value, which forms a new control algorithm of GPC. A networked control system based on Ethernet network was constructed, random-delay-time characteristic of data transmission was tested. Three control methods are compared in the system: PID, GPC, and GPC with error correction. GPC with error correction is verified to have the best performance of three methods.
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