基于T-S模糊模型的多变量预测控制  

MIMO Predictive Control Based on T-S Fuzzy Model

作　　者：牛林[1,2] 叶燎原[1] 李明德[3] 

机构地区：[1]昆明理工大学国土资源工程学院,昆明650093 [2]成都大学电子信息工程学院,成都610106 [3]阿坝州中等职业技术学校机电部,阿坝州623200

出　　处：《自动化与仪表》2009年第8期34-37,共4页Automation & Instrumentation

基　　金：成都市科技攻关项目(07GGYB198SF)

摘　　要：提出一种基于T-S模糊模型的多输入多输出预测控制策略。T-S模糊模型用于描述对象的非线性动态特性,模糊规则将非线性系统划分为多个局部子线性模型。为提高预测控制性能,采用多步线性化模型构成多步预报器,从而将预测控制中的非线性优化问题转化为一个线性二次寻优问题。串接贮槽液位控制系统的仿真结果表明,多步线性化模型预测控制性能优于单步线性化模型预测控制性能。A kind of MIMO nonlinear model predictive control strategy based on T-S fuzzy model is present. T-S fuzzy model is used to approximate the dynamics of nonlinear processes, local linear model of the nonlinear system can be derived from the fuzzy rule eonsequents in a straight forward way. To improve the predictive control perfor- mance multi-step hnearization around the working points within the prediction horizon is investigated and a multi- step fuzzy predictor is derived. Since the T-S fuzzy model can be treated as a linear time-vary system, the nonlin- ear program in the model predictive control turns into a linear quadratic problem. Simulation results on a MIMO liq- uid level process show the proposed approach using multi-step linearization of the T-S fuzzy model performs better than the one with single-step linearization.

关 键 词：模糊模型 非线性 预测控制 多输入多输出系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]