在基于二阶Adaline网络的广义预测极点配置控制器  

Generalized Predictive Pole Assignment Weighted Controller Based on Second-order Adaline Neural Network

作　　者：吕国芳[1] 王敏[1] 段向军[2] 

机构地区：[1]河海大学电气工程学院,江苏南京210098 [2]南京信息职业技术学院,江苏南京210046

出　　处：《系统仿真学报》2006年第z2期937-938,956,共3页Journal of System Simulation

摘　　要：为了解决实际应用中非线性被控过程的预测控制问题,把神经网络、广义预测控制和极点配置技术融为一体,提出一个新型自适应神经网络广义预测极点配置加权控制器(GPPWC)。首先提出非线性被控过程的二阶自适应线性神经元(Adaline)网络模型,然后给出基于二阶Adaline网络的GPPWC。仿真结果表明该方案的有效性。For solving predictive control questions of nonlinear system in practical application, the neural network, generalized predictive control and pole assignment technology were integrated, and a new adaptive neural network predictive pole assignment weighted controller was proposed. An adaptive linear neural network model was proposed, and the generalized predictive pole assignment weighted controller based on second-order Adaline Neural Network was given. Simulation result indicates its validity.

关 键 词：自适应线性神经元网络 广义预测控制 极点配置 加权控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]