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变风量空调系统是多变量,大滞后、非线性和不确定性的系统,普通的模糊神经网络控制已难以满足其多变量动态控制的要求,为改善变风量空调系统控制性能,本文提出了一种小波模糊神经网络预测控制方法,实现变风量空调的温湿度有效控制。通过小波神经网络预测器在线建立被控对象的数学模型,并用模糊RBF神经网络控制器对所得到的信息在线修正,优化控制器参数,从而改善系统的控制效果。仿真结果表明,小波模糊神经网络预测控制具有很强的鲁棒性和自适应能力,控制精度高,控制效果好,安全可靠等优点,具有广泛的应用价值。
VAV air conditioning system is a multivariable, large lag, nonlinear and uncertain system, the general fuzzy neural network control has been difficult to meet its multivariable dynamic control requirements, in order to improve the control performance of VAV air conditioning system, this paper presents a A Novel Fuzzy Neural Network Predictive Control Method to Realize Effective Control of Temperature and Humidity of VAV Air Conditioner. The mathematical model of the controlled object is established online by wavelet neural network predictor. The fuzzy RBF neural network controller is used to correct the information online and optimize the controller parameters to improve the control effect of the system. The simulation results show that the wavelet fuzzy neural network predictive control has a strong robustness and self-adaptive ability, high control accuracy, good control effect, safe and reliable, and has a wide range of applications.