摘要
针对供热过程耦合特性和节能控制的需要,提出了一种基于径向基函数(RBF)递归神经网络的供热解耦控制方法。通过典型信号响应与最小二乘结合的方法得到供热耦合系统模型,利用RBF递归神经网络进行解耦控制,消除了质调节、量调节通道间的非线性强耦合作用。仿真结果证明该方法具有良好的解耦控制特性,满足供热系统多回路控制的要求。
According to the coupling characteristics in heat supply process and the demands of energy saving control, proposes a novel heat supply decoupling method based on radial basis function （RBF） reeursion neural network. By establishing the heating coupling system model with typical signal response and least-square method, applies the RBF current neural network to eliminating the strong influence between quality-adjust and quantity-adjust channels. The simulation result shows that this method has a good decoupling performance and can meet the demands of multi-loop control of heating system.
出处
《暖通空调》
北大核心
2010年第2期128-132,127,共6页
Heating Ventilating & Air Conditioning
基金
国家"十一五"科技支撑计划重大项目(编号:2006BAJ03A04)
哈尔滨市科技创新人才研究专项资金项目(编号:RC2006XK007001)
关键词
供热过程
神经网络解耦
RBF递归神经网络
嵌入维数预估
heat supply process, neural network decoupling, RBF recursion neural network, embedding dimension estimation
