A Multi-model Predictive Control Strategy Based on Data-centric

被引：0
|
作者：
Zeng, Jing [1 ,2 ]
Xue, Ding-Yu [2 ]
Yuan, De-cheng [1 ]
机构：
[1] Shenyang Inst Chem Technol, Automat Dept, Shenyang 110142, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS | 2008年
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/ICNC.2008.845
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A multi-model predictive control strategy based on data-centric used to deal with control problem of strong nonlinear systems is proposed. Firstly a multi-model modeling method based on local models is given. The modeling idea is to find some data matching with the current working point from vast historical system input-output datasets, then to develop a local model using local polynomial fitting algorithm. With the change of working points, multiple local models are built. Then a multi-model predictive control strategy is developed by combining the obtained multiple models with predictive control, thus solves the control problem of a sort of unknown-structure nonlinear system which based on vast history data only. The simulation results of the designed control system show that the control strategy can obtain satisfactory performance.
引用
收藏
页码：313 / +
页数：2
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