Research Papers

Distributed Sliding-Mode Formation Controller Design for Multirobot Dynamic Systems

[+] Author and Article Information
Teh-Lu Liao

Department of Engineering Science,
National Cheng Kung University,
Tainan 70101, Taiwan
e-mail: tlliao@mail.ncku.edu.tw

Jun-Juh Yan

Department of Computer and Communication,
Shu-Te University,
Kaohsiung 82445, Taiwan
e-mail: jjyan@stu.edu.tw

Wei-Shou Chan

Materials and Electro-Optic Research Division,
National Chung-Shan Institute of
Science and Technology,
Taoyuan 32546, Taiwan
e-mail: wschan72417@gmail.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received June 4, 2015; final manuscript received December 21, 2016; published online April 13, 2017. Assoc. Editor: Azim Eskandarian.

J. Dyn. Sys., Meas., Control 139(6), 061008 (Apr 13, 2017) (7 pages) Paper No: DS-15-1255; doi: 10.1115/1.4035614 History: Received June 04, 2015; Revised December 21, 2016

This paper presents a distributed formation control for multirobot dynamic systems with external disturbances and system uncertainties. First from the Lagrangian analysis, the dynamic model of a wheeled mobile robot can be derived. Then, the robust distributed formation controller is proposed based on sliding-mode control, consensus algorithm, and graph theory. In this study, the robust stability of the closed-loop system is guaranteed by the Lyapunov stability theorem. From the simulation results, the proposed approach provides better formation responses compared to consensus algorithm.

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Grahic Jump Location
Fig. 1

Configuration diagram of a wheeled mobile robot

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Fig. 2

Communication topology of a leader–follower system

Grahic Jump Location
Fig. 3

Formation pattern (parallelogram)

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Fig. 4

Simulation results of consensus algorithm (CA) [29] for leader–follower formation control: (a) trajectory of each robot, (b) position errors of formation ep,xi(ep,yi), and (c) control input of each robot τLi(τRi)

Grahic Jump Location
Fig. 5

Simulation results of DSMFC (22) for leader–follower formation control: (a) trajectory of each robot, (b) position errors of formation ep,xi(ep,yi), and (c) control input of each robot τLi(τRi)

Grahic Jump Location
Fig. 6

Simulation results of DSMFC (35) (λ=0.01) for leader–follower formation control: (a) trajectory of each robot, (b) position errors of formation ep,xi(ep,yi), and (c) control input of each robot τLi(τRi)



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