非线性多变量零阶接近有界系统的多模型自适应控制

黄淼; 王昕; 王振雷

doi:10.3724/SP.J.1004.2014.02057

非线性多变量零阶接近有界系统的多模型自适应控制

doi: 10.3724/SP.J.1004.2014.02057

黄淼¹,
王昕²,
王振雷^1, ,

1.
华东理工大学化工过程先进控制和优化技术教育部重点实验室上海 200237;
2.
上海交通大学电工与电子技术中心上海 200240

基金项目:

国家重点基础研究发展计划（973计划）（2012CB720500），国家自然科学基金（61333010，61203157），中央高校基本科研业务费专项资金（上海市科技攻关项目）（12dz1125100），十二五国家科技支撑计划（2012BAF05B00），上海市重点学科建设项目（B504），流程工业综合自动化国家重点实验室开发课题资金资助

详细信息

作者简介:
黄淼华东理工大学信息科学与工程学院博士研究生.主要研究方向为多模型自适应控制.E-mail：huangmiao2010@126.com

通讯作者:
王振雷华东理工大学教授.主要研究方向为智能控制，复杂系统的建模及特征分析，故障诊断，智能优化算法.本文通信作者.E-mail：wangzhenl@ecust.edu.cn

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出版历程
- 收稿日期: 2013-07-23
- 修回日期: 2014-03-24
- 刊出日期: 2014-09-20

Multiple Model Adaptive Control for a Class of Nonlinear Multi-variable Systems with Zero-order Proximity Boundedness

1.
Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237;
2.
Center of Electrical & Electronic Technology, Shanghai Jiao Tong University, Shanghai 200240

Funds:

Supported by National Basic Research Program of China (973 Program)(2012CB720500), National Natural Science Foundation of China (61333010, 61203157), Fundamental Research Funds for the Central Universities (Scientific and Technological Project of Shanghai) (12dz1125100), National Five-year Science and Technology Plan & Technology Support (2012BAF05B00), Leading Academic Discipline Project of Shanghai (B504), and the State Key Laboratory of Synthetical Automation for Process Industries

摘要

摘要: 针对一类多变量非线性离散时间系统，提出一种新的基于神经网络的多模型自适应控制方法.为了将非线性系统的高阶非线性项的限制条件放宽到零阶接近有界，该方法引入了一种新的非线性模型.该模型在传统线性回归模型基础上增加了非线性补偿项，使模型的估计误差有界.一个神经网络模型与非线性模型同时被用来对系统进行辨识.基于性能指标的切换机构选择性能较好的模型对应的控制器对系统进行控制. 理论分析证明了零阶接近有界多模型自适应控制系统的有界输入和有界输出稳定性. 仿真实验说明了提出的多模型自适应控制方法的有效性.
- 零阶接近有界 /
- 多变量 /
- 非线性系统 /
- 多模型自适应控制
Abstract: A novel multiple model adaptive control method using neural networks is proposed for a class of MIMO nonlinear discrete-time systems. In order to relax the restriction of the higher order nonlinear term of the nonlinear system to zeroorder proximity boundedness, this method introduces a new nonlinear model. The model adds a nonlinear compensation term to the conventional linear autoregressive model such that the estimation error is bounded. A neural network model is used to identify the system with nonlinear model simultaneously. A performance-based switching mechanism determines the controller which has the better performance to control the system. Theoretic analysis proves the bounded-input-boundedoutput stability of the zero-order proximity boundedness multiple model adaptive control system. Simulation results are presented to show the effectiveness of the proposed method.
- Zero order proximity boundedness /
- multi-variable /
- nonlinear system /
- multiple model adaptive control

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参考文献(24)

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非线性多变量零阶接近有界系统的多模型自适应控制

doi: 10.3724/SP.J.1004.2014.02057

作者简介:
黄淼华东理工大学信息科学与工程学院博士研究生.主要研究方向为多模型自适应控制.E-mail：huangmiao2010@126.com

通讯作者:
王振雷华东理工大学教授.主要研究方向为智能控制，复杂系统的建模及特征分析，故障诊断，智能优化算法.本文通信作者.E-mail：wangzhenl@ecust.edu.cn

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Multiple Model Adaptive Control for a Class of Nonlinear Multi-variable Systems with Zero-order Proximity Boundedness

计量

目录

留言板

非线性多变量零阶接近有界系统的多模型自适应控制

doi: 10.3724/SP.J.1004.2014.02057

作者简介: 黄淼 华东理工大学信息科学与工程学院博士研究生.主要研究方向为多模型自适应控制.E-mail：huangmiao2010@126.com

通讯作者: 王振雷 华东理工大学教授.主要研究方向为智能控制，复杂系统的建模及特征分析，故障诊断，智能优化算法.本文通信作者.E-mail：wangzhenl@ecust.edu.cn

计量

出版历程

Multiple Model Adaptive Control for a Class of Nonlinear Multi-variable Systems with Zero-order Proximity Boundedness

计量

出版历程

目录

作者简介:
黄淼华东理工大学信息科学与工程学院博士研究生.主要研究方向为多模型自适应控制.E-mail：huangmiao2010@126.com

通讯作者:
王振雷华东理工大学教授.主要研究方向为智能控制，复杂系统的建模及特征分析，故障诊断，智能优化算法.本文通信作者.E-mail：wangzhenl@ecust.edu.cn