Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance

Qun Cao; Yuanqing Xia; Zhongqi Sun; Hongru Jiang; Xiaopeng Liu

doi:10.1109/DDCLS.2018.8515961

Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance

Qun Cao
, Yuanqing Xia
, Zhongqi Sun
, Hongru Jiang
, Xiaopeng Liu

自动化学院

Beijing Institute of Technology
CAST

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

In this paper, we present a self-triggered model predictive control (MPC) scheme for unicycle robots with coupled input constraint and bounded external disturbances. Firstly, based on Lyapunov theory, a self-triggered mechanism is developed to the aim of reducing the computation load of MPC. Secondly, by designing a robust terminal region and proper parameters, stability of the closed-loop system as well as a sub-optimal performance are guaranteed. In addition, we compare the given self-triggered MPC scheme with the traditional one. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed strategy.

源语言	英语
主期刊名	Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018
出版商	Institute of Electrical and Electronics Engineers Inc.
页	860-865
页数	6
ISBN（电子版）	9781538626184
DOI	https://doi.org/10.1109/DDCLS.2018.8515961
出版状态	已出版 - 30 10月 2018
活动	7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018 - Enshi, Hubei Province, 中国期限: 25 5月 2018 → 27 5月 2018

出版系列

姓名	Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

会议

会议	7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018
国家/地区	中国
市	Enshi, Hubei Province
时期	25/05/18 → 27/05/18

访问文件

10.1109/DDCLS.2018.8515961

其它文件与链接

链接到 Scopus 的出版物

引用此

Cao, Q., Xia, Y., Sun, Z., Jiang, H., & Liu, X. (2018). Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance. 在 Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018 (页码 860-865). 文章 8515961 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DDCLS.2018.8515961

Cao, Qun ; Xia, Yuanqing ; Sun, Zhongqi 等. / Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance. Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 860-865 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018).

@inproceedings{aaf81c194e5e46ae9bd84f15befb3f71,

title = "Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance",

abstract = "In this paper, we present a self-triggered model predictive control (MPC) scheme for unicycle robots with coupled input constraint and bounded external disturbances. Firstly, based on Lyapunov theory, a self-triggered mechanism is developed to the aim of reducing the computation load of MPC. Secondly, by designing a robust terminal region and proper parameters, stability of the closed-loop system as well as a sub-optimal performance are guaranteed. In addition, we compare the given self-triggered MPC scheme with the traditional one. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed strategy.",

keywords = "Bounded external disturbances, Input constraint, Model predictive control, Self-triggered, Unicycle robots",

author = "Qun Cao and Yuanqing Xia and Zhongqi Sun and Hongru Jiang and Xiaopeng Liu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018 ; Conference date: 25-05-2018 Through 27-05-2018",

year = "2018",

month = oct,

day = "30",

doi = "10.1109/DDCLS.2018.8515961",

language = "English",

series = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "860--865",

booktitle = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",

address = "United States",

}

Cao, Q, Xia, Y , Sun, Z, Jiang, H & Liu, X 2018, Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance. 在 Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018., 8515961, Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018, Institute of Electrical and Electronics Engineers Inc., 页码 860-865, 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018, Enshi, Hubei Province, 中国, 25/05/18. https://doi.org/10.1109/DDCLS.2018.8515961

Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance. / Cao, Qun; Xia, Yuanqing ; Sun, Zhongqi 等.
Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 860-865 8515961 (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance

AU - Cao, Qun

AU - Xia, Yuanqing

AU - Sun, Zhongqi

AU - Jiang, Hongru

AU - Liu, Xiaopeng

PY - 2018/10/30

Y1 - 2018/10/30

N2 - In this paper, we present a self-triggered model predictive control (MPC) scheme for unicycle robots with coupled input constraint and bounded external disturbances. Firstly, based on Lyapunov theory, a self-triggered mechanism is developed to the aim of reducing the computation load of MPC. Secondly, by designing a robust terminal region and proper parameters, stability of the closed-loop system as well as a sub-optimal performance are guaranteed. In addition, we compare the given self-triggered MPC scheme with the traditional one. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed strategy.

AB - In this paper, we present a self-triggered model predictive control (MPC) scheme for unicycle robots with coupled input constraint and bounded external disturbances. Firstly, based on Lyapunov theory, a self-triggered mechanism is developed to the aim of reducing the computation load of MPC. Secondly, by designing a robust terminal region and proper parameters, stability of the closed-loop system as well as a sub-optimal performance are guaranteed. In addition, we compare the given self-triggered MPC scheme with the traditional one. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed strategy.

KW - Bounded external disturbances

KW - Input constraint

KW - Model predictive control

KW - Self-triggered

KW - Unicycle robots

UR - https://www.scopus.com/pages/publications/85056999734

U2 - 10.1109/DDCLS.2018.8515961

DO - 10.1109/DDCLS.2018.8515961

M3 - Conference contribution

AN - SCOPUS:85056999734

T3 - Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

SP - 860

EP - 865

BT - Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018

Y2 - 25 May 2018 through 27 May 2018

ER -

Cao Q, Xia Y , Sun Z, Jiang H, Liu X. Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance. 在 Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 页码 860-865. 8515961. (Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018). doi: 10.1109/DDCLS.2018.8515961

Self-triggered MPC for tracking of constrained wheeled robots with additive disturbance

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