Research Papers

Formation Tracking Control of Second-Order Multi-Agent Systems With Time-Varying Delay

[+] Author and Article Information
Tao Li

School of Automation Engineering,
Nanjing University of Aeronautics
and Astronautics,
Nanjing 211106, China
e-mail: autolitao@nuaa.edu.cn

Zhipeng Li

School of Automation Engineering,
Nanjing University of Aeronautics
and Astronautics,
Nanjing 211106, China
e-mail: lizhipeng12300@163.com

Haitao Zhang

College of National Defense Engineering,
The Army Engineering University of PLA,
Nanjing 210007, China
e-mail: zhtnanjing@126.com

Shumin Fei

Key Laboratory of Measurement and
Control of CSE,
School of Automation, Southeast University,
Ministry of Education,
Nanjing 210096, China
e-mail: smfei@seu.edu.cn

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received November 17, 2017; final manuscript received May 17, 2018; published online June 26, 2018. Assoc. Editor: Ming Xin.

J. Dyn. Sys., Meas., Control 140(11), 111015 (Jun 26, 2018) (11 pages) Paper No: DS-17-1568; doi: 10.1115/1.4040327 History: Received November 17, 2017; Revised May 17, 2018

This paper considers the problem on formation tracking control of second-order multi-agent systems (MASs) with communication time-varying delay. Sufficient conditions on the directed interaction topology and existence of the feedback gains to ensure the desired control are presented. Through choosing two augmented Lyapunov–Krasovskii (L–K) functionals and using some novel Wirtinger-based integral inequalities, the previously ignored information can be reconsidered and the application area of derived results can be greatly extended. Moreover, a novel constructive technique is given to compute out the controller gain by resorting to solving the achieved linear matrix inequalities (LMIs). Finally, a numerical example with comparisons and simulations is provided to illustrate the obtained results.

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Grahic Jump Location
Fig. 1

Directed interaction topology G

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Fig. 2

The asymptotically stability of tracking error system (29)

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Fig. 3

The trajectories of five agents within t=150 s

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Fig. 4

The trajectory snapshots at t=100s when τm=0.480 and μm=0.3

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Fig. 5

The asymptotically stability of tracking error system (29) along x and y-axis

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Fig. 6

The trajectories of position and velocity along x-axis

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Fig. 7

The trajectory of position and velocity along y-axis



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