A suboptimal model predictive formation control

Dongbing Gu; Erfu Yang

doi:10.1109/IROS.2005.1545536

A suboptimal model predictive formation control

Dongbing Gu^*, Erfu Yang

^*Corresponding author for this work

Design, Manufacturing And Engineering Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

13 Citations (Scopus)

Abstract

We investigate the leader-following formation control of mobile robots through the Model Predictive Control (MPC) in this paper. We establish its control stability by adding a terminal state penalty to the cost function and a terminal state region to the optimisation constraints. We also design a terminal state region based on an input-output feedback linearisation controller for the MPC. A suboptimal stable solution is sought to reduce the computational time used in the MPC. Simulations on the control are provided to verify the proposed control strategy.

Original language	English
Title of host publication	2005 IEEE/RSJ International Conference on Intelligent Robots and Systems
Place of Publication	Piscataway, NJ.
Publisher	IEEE
Pages	1295-1300
Number of pages	6
ISBN (Print)	0780389123
DOIs	https://doi.org/10.1109/IROS.2005.1545536
Publication status	Published - May 2005
Event	IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 - Edmonton, AB, United Kingdom Duration: 2 Aug 2005 → 6 Aug 2005

Conference

Conference	IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005
Country/Territory	United Kingdom
City	Edmonton, AB
Period	2/08/05 → 6/08/05

Keywords

formation control
leader-following control model predictive control
nonholonomic mobile robots
feedback
linearisation techniques
mobile robots
optimal control
predictive control
stability

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10.1109/IROS.2005.1545536

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title = "A suboptimal model predictive formation control",

abstract = "We investigate the leader-following formation control of mobile robots through the Model Predictive Control (MPC) in this paper. We establish its control stability by adding a terminal state penalty to the cost function and a terminal state region to the optimisation constraints. We also design a terminal state region based on an input-output feedback linearisation controller for the MPC. A suboptimal stable solution is sought to reduce the computational time used in the MPC. Simulations on the control are provided to verify the proposed control strategy. ",

keywords = "formation control, leader-following control model predictive control, nonholonomic mobile robots, feedback, linearisation techniques, mobile robots, optimal control, predictive control, stability",

author = "Dongbing Gu and Erfu Yang",

year = "2005",

month = may,

doi = "10.1109/IROS.2005.1545536",

language = "English",

isbn = "0780389123",

pages = "1295--1300",

booktitle = "2005 IEEE/RSJ International Conference on Intelligent Robots and Systems",

publisher = "IEEE",

note = "IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 ; Conference date: 02-08-2005 Through 06-08-2005",

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AU - Yang, Erfu

PY - 2005/5

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N2 - We investigate the leader-following formation control of mobile robots through the Model Predictive Control (MPC) in this paper. We establish its control stability by adding a terminal state penalty to the cost function and a terminal state region to the optimisation constraints. We also design a terminal state region based on an input-output feedback linearisation controller for the MPC. A suboptimal stable solution is sought to reduce the computational time used in the MPC. Simulations on the control are provided to verify the proposed control strategy.

AB - We investigate the leader-following formation control of mobile robots through the Model Predictive Control (MPC) in this paper. We establish its control stability by adding a terminal state penalty to the cost function and a terminal state region to the optimisation constraints. We also design a terminal state region based on an input-output feedback linearisation controller for the MPC. A suboptimal stable solution is sought to reduce the computational time used in the MPC. Simulations on the control are provided to verify the proposed control strategy.

KW - formation control

KW - leader-following control model predictive control

KW - nonholonomic mobile robots

KW - feedback

KW - linearisation techniques

KW - mobile robots

KW - optimal control

KW - predictive control

KW - stability

UR - https://www.scopus.com/pages/publications/79957987082

UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=10375

U2 - 10.1109/IROS.2005.1545536

DO - 10.1109/IROS.2005.1545536

M3 - Conference contribution book

AN - SCOPUS:79957987082

SN - 0780389123

SP - 1295

EP - 1300

BT - 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems

PB - IEEE

CY - Piscataway, NJ.

T2 - IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005

Y2 - 2 August 2005 through 6 August 2005

ER -

A suboptimal model predictive formation control

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