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基于混合逻辑的非线性系统多模型预测控制
引用本文:邹涛,王昕,李少远.基于混合逻辑的非线性系统多模型预测控制[J].自动化学报,2007,33(2):188-192.
作者姓名:邹涛  王昕  李少远
作者单位:1. 上海交通大学自动化研究所 上海 200240
2. 上海交通大学电工与电子技术中心 上海 200240
基金项目:国家自然科学基金;上海市科委资助项目;新世纪优秀人才支持计划
摘    要:针对已有的多模型预测控制算法在模型预测过程中采用局部线性模型进行预测而产生的预测误差较大这一问题, 本文将非线性过程的多模型描述与输出预测之间的因果关系以约束条件的形式引入到模型预测控制的设计中, 将非线性过程描述成为一个混合逻辑动态系统模型, 模型切换规则以先验知识的形式引入到多模型预测过程中, 该模型可以全局地表征非线性过程的特性, 从而解决了多模型约束非线性预测控制的模型预测与模型切换问题.

关 键 词:非线性预测控制  多模型  混合逻辑  混合整数二次规划(MIQP)
收稿时间:2005-09-12
修稿时间:2006-03-31

Multi-Model Predictive Control for Nonlinear Systems Based on Mixed Logic
ZOU Tao,WANG Xin,LI Shao-Yuan.Multi-Model Predictive Control for Nonlinear Systems Based on Mixed Logic[J].Acta Automatica Sinica,2007,33(2):188-192.
Authors:ZOU Tao  WANG Xin  LI Shao-Yuan
Institution:1. Institute of Automation, Shanghai Jiao Tong University, Shanghai 200240
2. Center of Electrical and Electronics Engineering, Shanghai Jiao Tong University, Shanghai 200240
Abstract:Big prediction errors are brought into being as the local linear model is used to predict the future output m the model prediction process for the existent multi-model predictive control algorithms. To solve this problem, this paper introduces causality relationship between multi-model of nonlinear process and output prediction into model predictive control framework in the term of constraint conditions, so that the nonlinear process can be described by a mixed-logic dynamic model. This paper also introduces switch rules into the multi-model predictive controller as a kind of pre- experiential knowledge. This new mixed logic dynamic model can characterize the nonlinear process entirely, thus solving the problem of model prediction and model switch for multi-model constrained nonlinear predictive control.
Keywords:Nonlinear predictive control  multiple models  mixed logic  mixed integer quadratic program
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