递归神经网络在供热解耦控制中的应用
Application of RBF recursion neural network to heat supply decoupling control
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。
Abstract：
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) recursion 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.
Keywords:heatsupplyprocess,neuralnetworkdecoupling,RBFrecursionneuralnetwork,embeddingdimensionestimation