摘要
将模糊控制与神经网络相结合,设计4层模糊神经网络控制器,分析其结构及算法。利用神经网络的自学习能力,在线动态调整模糊变量的隶属函数,优化控制规则,并对曝气池中溶解氧浓度与活性污泥浓度进行控制。通过Matlab对溶解氧的控制进行数字仿真实验,结果表明,具有学习能力的模糊神经网络控制可在污水处理系统的应用中获得更优的性能。
This paper combines fuzzy control with nerve network,designs 4-layers fuzzy neural network controllers,analyzes the structure and algorithm in detail,uses self-study ability of nerve network,on-line and dynamic adjusts the variable of membership function.It optimizes its control rules,and makes the concentration of dissolved oxygen and activated sludge under control.The paper designs fuzzy neural network controllers and respectively applies them to the control of dissolved oxygen,and simulates the fuzzy controllers.Results indicate that the fuzzy neural network controllers with self-study ability are better capability in wastewater treatment system.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第8期203-205,共3页
Computer Engineering
基金
苏州职业大学科研基金资助项目(JDX0908)
关键词
模糊神经网络
智能控制
序批式活性污泥法
溶解氧
fuzzy neural network
intelligent control
Sequencing Batch Reactor（SBR）
Dissolved Oxygen（DO）
