针对网络控制系统(NCS)具有不确定时延的特性，提出了将广义预测控制(GPC)应用于网络控制系统的思想。为了克服模型失配和系统不确定性的影响，基于BP神经网络建立一个误差的预测模型，用误差预测值对输出预测值进行补偿，构成新型的广义预测控制算法，并采用了平滑滤波的加权输入控制律。在网络控制系统中，测试了网络数据传输的随机延迟时间特性，比较了GPC和具有BP网络预测误差补偿的GPC两种控制方法，验证了具有BP网络预测误差补偿的GPC在模型失配时的更好的控制性能。

With regard to the characteristics of uncertain network-induced delay, an idea of using Generalized Predictive Control (GPC) is proposed in networked control systems. To overcome the influence of modeling mismatch and uncertainty of a 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, and smooth filtering weighted controlled input variable is adopted. Random-delay-time characteristic of data transmission is tested in a networked control system. GPC and GPC with error compensation are compared in the system. GPC with BP error compensation is verified to have better performance in a modeling mismatch system.