Recursive Subspace-based Predictive Control and Its Application to Fault-tolerant Control

被引：4

作者：

Gao, Jingjing ^{[1
]}

Yang, Xu ^{[1
]}

Li, Linlin ^{[1
]}

Luo, Hao ^{[2
]}

Ding, Steven X. ^{[3
]}

Zhang, Kai ^{[1
]}

Peng, Kaixiang ^{[1
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

[2] Harbin Inst Technol, Sch Astronaut, Harbin 150001, Heilongjiang, Peoples R China

[3] Univ Duisburg Essen, Inst Automat Control & Complex Syst, Fac Engn, D-47057 Duisburg, Germany

来源：

IFAC PAPERSONLINE | 2018年 / 51卷 / 24期

基金：

中国国家自然科学基金; 北京市自然科学基金; 国家重点研发计划;

关键词：

Data-driven predictive control; closed-loop subspace predictor; recursive algorithm; fault-tolerant control; SYSTEM-IDENTIFICATION;

D O I：

10.1016/j.ifacol.2018.09.651

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the data-driven realization of predictive controllers, and its application to fault-tolerant control. With the aid of subspace identification method, the subspace predictor is first derived in the closed-loop setup. To cope with the change in the process, a recursive algorithm is adopted to recursive update the subspace matrices. The data-driven predictive controller is designed by seeking the solution of the quadratic programming problem, without the information of the predesigned controller. Then, it is applied to fault-tolerant control by implementing the recursive subspace predictor. In the end, the effectiveness of the proposed method is verified by a case study on the three-tank system. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：696 / 702

页数：7

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