基于C-R模糊模型的非线性预测控制  

C-R Fuzzy Model Based Nonlinear Predictive Control

作　　者：刘军[1] 段培永[2] 许晓鸣[3] 

机构地区：[1]青岛化工学院信控学院,青岛266042 [2]山东建筑工程学院自动化系,山东250014 [3]上海交通大学自动化研究所,上海200030

出　　处：《系统仿真学报》2002年第2期250-252,共3页Journal of System Simulation

摘　　要：Cao和Ress 提出的模糊模型(称为C-R模糊模型)由模糊推理和局部线性解析模型两部分组成,用隶属函数加权局部模型构成系统的全局非线性模型。本文提出了一种新的结构上与阶跃模型相类似的C-R模糊阶跃模型,并用DMC动态矩阵控制算法,求解基于该模型的非线性预测控制问题, 得出了预测控制算法的解析形式,该方法克服了一般非线性预测控制算法求解困难的缺陷。The fuzzy model presented by Cao and Ress is composed of fuzzy inference and local analytical model, and the global nonlinear model is the weighted sum of the local models with the respective membership functions. In the paper, a novel C-R fuzzy step model is given, its structure is similar to step response model. The analytical algorithm of a nonlinear predictive control is obtained through solving the problem of nonlinear predictive control based on the given model by means of dynamic matrix control (DMC) algorithm. The method can be used to solve the problem of a general nonlinear predictive control easily.

关 键 词：非线性预测控制 C-R模糊模型 仿真 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] O231[自动化与计算机技术—控制科学与工程]