基于模糊神经网络融合的温度控制方法

针对目前温度控制中存在的问题，研究设计了一种新的适合于非线性、惯性系统应用的动态控制的方法。采用了将具有简单有效的非线性控制作用的模糊控制技术与学习和自适应能力较强的人工神经网络技术相融合的方法，建立了模糊神经网络相融合的智能控制模型。文章详细地介绍了基于模糊神经网络的智能温度控制的实现过程。实际应用结果表明，系统具有较强的实时性和可靠性，不仅温度控制精度高，而且动态响应速度快。该控制方法的研究，为实现最佳温度控制提供了理论根据和有效方法。

A method of temperature control systems based on fusion combined with fuzzy neural network

According to the problem of temperature control systems at present, then a novel dynamic control method are researched and designed ,which is suitable for nonlinear and time-dependent systems. A fusion method that is combined fuzzy controlling, which is simple and effective, with neural network technique, which is able of self-adjustment, are adopted. A intelligence model of fuzzy neural network fusion are established. The realization process of the fuzzy neural network fusion method for intelligence temperature controlling is given and it is also explained in detail in this paper. The result of application is high real time and dependability in this system. And not only is it high precision of temperature control, but also it is quick dynamic respond. This investigation on controlling method provides basic theory and effective way for the optimized control of temperature systems.