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MIMO系统的多模型预测控制
引用本文:李柠,李少远,席裕庚.MIMO系统的多模型预测控制[J].自动化学报,2003,29(4):516-523.
作者姓名:李柠  李少远  席裕庚
作者单位:1.上海交通大学自动化研究所,上海
基金项目:NationalNaturalScienceFoundationofP.R.China(6 99340 2 0and 6 0 0 74 0 0 4 )
摘    要:针对非线性多变量系统提出一种多模型预测控制(MMPC)策略.首先给出一种多模型 辨识方法,利用模糊满意聚类算法将复杂非线性系统划分为若干子系统,并获得多个线性模型, 通过模型变换得出全局系统模型,接着对全局MIMO系统设计MMPC,并进行了系统的性能分 析,最后以pH中和过程为例,通过仿真研究验证了辨识和控制算法的有效性.

关 键 词:MIMO系统    多模型    模型预测控制(MPC)    模糊满意聚类    pH中和过程
收稿时间:2002-5-8

Multiple Model Predictive Control for MIMO Systems
LI Ning,LI Shao-Yuan,XI Yu-Geng.Multiple Model Predictive Control for MIMO Systems[J].Acta Automatica Sinica,2003,29(4):516-523.
Authors:LI Ning  LI Shao-Yuan  XI Yu-Geng
Affiliation:1.Institute of Automation,Shanghai Jiaotong University,Shanghai
Abstract:A multi model based predictive control (MMPC) strategy dealing with nonlinear model based predictive control (NMPC) for MIMO systems is developed in this paper. Firstly a multi model identification method is given. Using fuzzy satisfactory clustering algorithm presented in this paper, the complex nonlinear system can be quickly divided into multiple fuzzy parts. A global model can be obtained by some transformation of the obtained multiple linear models. An MMPC algorithm is therefore designed for the global MIMO systems with system performance analysis. Taking a pH neutralization control system as simulation example, the simulation results verify the effectiveness of MMPC on complex nonlinear systems.
Keywords:MIMO systems  multi  model  model  based predictive control (MPC)  fuzzy satisfactory clustering  pH neutralization process
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