室内温度模糊神经控制策略研究  

Research on Fuzzy Neural Network Control for Temperature Indoor System

作　　者：龙凤[1] 程绪建[1] 陈桂明[1] 苗硕[2] 

机构地区：[1]第二炮兵工程学院,陕西西安710025 [2]西安微电子技术研究所,陕西西安710054

出　　处：《微电子学与计算机》2009年第8期226-229,共4页Microelectronics & Computer

摘　　要：采用模糊神经控制器建立了室温控制系统模型.用遗传算法优化了模糊神经控制器的结构和参数,采用三段式遗传编码方式,有效地将隶属度函数和控制规则映射到遗传算法的搜索空间.实验结果表明,文中策略比一般的模糊神经控制在调节时间以及减少误差方面具有较好的性能.We build a temperature indoor control system model basing on adaptive fuzzy neural network. We research on an optima/fuzzy neural network controller by using genetic algorithm. We use the three - fragment code method to map the membership functions and the control rules of the fuzzy neural network controller into the search space of genetic algorithm. The results of simulation experiment demonstrated that compared with traditional fuzzy neural network controller, our strategy has better performance in terms of adjusting latency and inaccuracy reduction.

关 键 词：遗传算法 模糊神经网络 温度控制 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]