针对可控受限的多变量耦合系统,采用改进BP算法,基于BP神经网络建立了多变量炉温控制系统的神经网络预测模型.仿真结果表明,BP神经网络能够较好的描述多变量炉温控制系统中的耦合关系,预测模型简单,是理想的多变量非线性系统模型辨识网络.“,”According to limited controllability multivariable coupling system,the neural network forecasting model of the multivariable furnace temperature control system is established. The neural network forecasting model is tested by the testing sample sets. The real identification result indicates that the BP neural network model describes coupling relationship of the multivariable furnace temperature control system and suits identification of nonlinear systems.