| 非线性多变量零阶接近有界系统的多模型自适应控制 |
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| 引用本文： | 黄淼, 王昕, 王振雷. 非线性多变量零阶接近有界系统的多模型自适应控制. 自动化学报, 2014, 40(9): 2057-2065. doi: 10.3724/SP.J.1004.2014.02057 |
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| 作者姓名： | 黄淼 王昕 王振雷 |
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| 作者单位： | 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 |
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| 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 |
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| 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.
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| 关 键 词： | 零阶接近有界 多变量 非线性系统 多模型自适应控制 |
| 收稿时间： | 2013-07-23 |
| 修稿时间： | 2014-03-24 |
Multiple Model Adaptive Control for a Class of Nonlinear Multi-variable Systems with Zero-order Proximity Boundedness |
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| HUANG Miao, WANG Xin, WANG Zhen-Lei. Multiple Model Adaptive Control for a Class of Nonlinear Multi-variable Systems with Zero-order Proximity Boundedness. ACTA AUTOMATICA SINICA, 2014, 40(9): 2057-2065. doi: 10.3724/SP.J.1004.2014.02057 |
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| Authors: | HUANG Miao WANG Xin WANG Zhen-Lei |
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| Affiliation: | 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 |
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| 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. |
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| Keywords: | Zero order proximity boundedness multi-variable nonlinear system multiple model adaptive control |
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