New model predictive control for improved disturbance rejection

Xian Li; Shuai Liu; Kok Kiong Tan; Qing Guo Wang

doi:10.1109/ChiCC.2016.7554023

New model predictive control for improved disturbance rejection

Xian Li
, Shuai Liu
, Kok Kiong Tan
, Qing Guo Wang

Electrical and Electronic Engineering Science

National University of Singapore
Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In industrial systems, measurable but controllable disturbances are common and may drive systems away from their references. In standard MPC, its output prediction will have large errors due to these disturbances and thus cause poor regulation performance. In this paper, a complete plant model with disturbance dynamics is considered for better output prediction in MPC so as to improve its regulation. Since unknown future disturbances are also involved, they can be predicted from their past values. To verify its efficiency, a permanent magnet synchronous motor is simulated and shows significant improvement in disturbance rejection in comparison to the integral MPC and classical feedforward control.

Original language	English
Title of host publication	Proceedings of the 35th Chinese Control Conference, CCC 2016
Editors	Jie Chen, Qianchuan Zhao, Jie Chen
Publisher	IEEE Computer Society
Pages	4318-4323
Number of pages	6
ISBN (Electronic)	9789881563910
DOIs	https://doi.org/10.1109/ChiCC.2016.7554023
Publication status	Published - 26 Aug 2016
Event	35th Chinese Control Conference, CCC 2016 - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016

Publication series

Name	Chinese Control Conference, CCC
Volume	2016-August
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	35th Chinese Control Conference, CCC 2016
Country/Territory	China
City	Chengdu
Period	27/07/16 → 29/07/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Disturbance prediction
MPC
SQP
regulation control

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Computer Science Applications
Applied Mathematics

Access to Document

10.1109/ChiCC.2016.7554023

Cite this

@inproceedings{33858174d3d94f73a788ff93bb07ca1b,

title = "New model predictive control for improved disturbance rejection",

abstract = "In industrial systems, measurable but controllable disturbances are common and may drive systems away from their references. In standard MPC, its output prediction will have large errors due to these disturbances and thus cause poor regulation performance. In this paper, a complete plant model with disturbance dynamics is considered for better output prediction in MPC so as to improve its regulation. Since unknown future disturbances are also involved, they can be predicted from their past values. To verify its efficiency, a permanent magnet synchronous motor is simulated and shows significant improvement in disturbance rejection in comparison to the integral MPC and classical feedforward control.",

keywords = "Disturbance prediction, MPC, SQP, regulation control",

author = "Xian Li and Shuai Liu and Tan, \{Kok Kiong\} and Wang, \{Qing Guo\}",

note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",

year = "2016",

month = aug,

day = "26",

doi = "10.1109/ChiCC.2016.7554023",

language = "English",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "4318--4323",

editor = "Jie Chen and Qianchuan Zhao and Jie Chen",

booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",

address = "United States",

}

Li, X, Liu, S, Tan, KK & Wang, QG 2016, New model predictive control for improved disturbance rejection. in J Chen, Q Zhao & J Chen (eds), Proceedings of the 35th Chinese Control Conference, CCC 2016., 7554023, Chinese Control Conference, CCC, vol. 2016-August, IEEE Computer Society, pp. 4318-4323, 35th Chinese Control Conference, CCC 2016, Chengdu, China, 27/07/16. https://doi.org/10.1109/ChiCC.2016.7554023

New model predictive control for improved disturbance rejection. / Li, Xian; Liu, Shuai; Tan, Kok Kiong et al.
Proceedings of the 35th Chinese Control Conference, CCC 2016. ed. / Jie Chen; Qianchuan Zhao; Jie Chen. IEEE Computer Society, 2016. p. 4318-4323 7554023 (Chinese Control Conference, CCC; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - New model predictive control for improved disturbance rejection

AU - Li, Xian

AU - Liu, Shuai

AU - Tan, Kok Kiong

AU - Wang, Qing Guo

PY - 2016/8/26

Y1 - 2016/8/26

N2 - In industrial systems, measurable but controllable disturbances are common and may drive systems away from their references. In standard MPC, its output prediction will have large errors due to these disturbances and thus cause poor regulation performance. In this paper, a complete plant model with disturbance dynamics is considered for better output prediction in MPC so as to improve its regulation. Since unknown future disturbances are also involved, they can be predicted from their past values. To verify its efficiency, a permanent magnet synchronous motor is simulated and shows significant improvement in disturbance rejection in comparison to the integral MPC and classical feedforward control.

AB - In industrial systems, measurable but controllable disturbances are common and may drive systems away from their references. In standard MPC, its output prediction will have large errors due to these disturbances and thus cause poor regulation performance. In this paper, a complete plant model with disturbance dynamics is considered for better output prediction in MPC so as to improve its regulation. Since unknown future disturbances are also involved, they can be predicted from their past values. To verify its efficiency, a permanent magnet synchronous motor is simulated and shows significant improvement in disturbance rejection in comparison to the integral MPC and classical feedforward control.

KW - Disturbance prediction

KW - MPC

KW - SQP

KW - regulation control

UR - https://www.scopus.com/pages/publications/84987922682

U2 - 10.1109/ChiCC.2016.7554023

DO - 10.1109/ChiCC.2016.7554023

M3 - Conference contribution

AN - SCOPUS:84987922682

T3 - Chinese Control Conference, CCC

SP - 4318

EP - 4323

BT - Proceedings of the 35th Chinese Control Conference, CCC 2016

A2 - Chen, Jie

A2 - Zhao, Qianchuan

A2 - Chen, Jie

PB - IEEE Computer Society

T2 - 35th Chinese Control Conference, CCC 2016

Y2 - 27 July 2016 through 29 July 2016

ER -

New model predictive control for improved disturbance rejection

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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