变风量空调系统的模糊神经网络预测控制

针对变风量中央空调系统具有多变量、大滞后和非线性的系统特性及常规控制算法系统响应慢、控制精度不高等问题，提出了模糊神经网络预测控制策略.该方法将模糊神经网络控制与预测控制技术相结合，建立了模糊神经网络与预测控制结合的复合控制器模型，通过优化变风量控制方式，有效地实现了中央空调系统的预测控制.结果表明，该控制方法能使系统具有良好的动态性能和稳态性能，控制精度高，节能效果显著，具有广泛的应用前景.

Fuzzy neural network predictive control for VAV air conditioning system

Aiming at the problems that the variable air volume （VAV） central air conditioning system has such characteristics as multi variables, large time delay and nonlinearity and the routine control algorithm exhibits such disadvantages as slow system response and low control precision, a fuzzy neural network predictive control strategy was proposed. The fuzzy neural network control was combined with the predictive control technology in the proposed method, and a compound controller model combining both fuzzy neural network and predictive control was established. Through optimizing the control mode of VAV, the predictive control of central air conditioning system was effectively realized. The results show that with adopting the proposed control method, the system exhibits good dynamic and steady performances, high control precision, obvious energy saving effect and wide application prospect.