Please wait a minute...
Chin. Phys. B, 2014, Vol. 23(2): 028901    DOI: 10.1088/1674-1056/23/2/028901
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Prev   Next  

Generation of minimally persistent circle formation for a multi-agent system

Luo Xiao-Yuan (罗小元)a, Shao Shi-Kai (邵士凯)a, Zhang Yu-Yan (张玉燕)a, Li Shao-Bao (李绍宝)b, Guan Xin-Ping (关新平)a, Liu Zhi-Xin (刘志新)a
a School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
b Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China
Abstract  In this paper, two methods of generating minimally persistent circle formation are presented. The proposed methods adopt a leader-follower strategy and all followers are firstly motivated to move into the leader’s interaction range. Based on the information about relative angle and relative distance, two numbering schemes are proposed to generate minimally persistent circle formation. Distributed control laws are also designed to maintain the desired relative distance between agents. The distinctive features of the proposed methods are as follows. First, only 2n-3 unilateral communication links for n agents are needed during the circle formation process and thus the communication complexity can be reduced. In addition, the formation topology is kept fixed for the whole motion and achieves a self-stability property. Finally, each follower keeps a regualr interval with its neighbors and the formation converges to a uniform circle formation. Simulation results are also provided to demonstrate the effectiveness of the proposed methods.
Keywords:  multiagent system      formation control      minimally persistent graph      numbering strategy  
Received:  13 January 2013      Revised:  10 July 2013      Accepted manuscript online: 
PACS:  89.20.Ff (Computer science and technology)  
  87.85.St (Robotics)  
  89.65.Ef (Social organizations; anthropology ?)  
  02.30.Em (Potential theory)  
Fund: Project supported by the National Basic Research Program of China (Grant No. 2010CB731800), the National Natural Science Foundation of China (Grant Nos. 60934003, 61074065, and 61375105), and the Natural Science Foundation of Hebei Province, China (Grant No. F2012203119).
Corresponding Authors:  Liu Zhi-Xin     E-mail:  lzxauto@ysu.edu.cn
About author:  89.20.Ff; 87.85.St; 89.65.Ef; 02.30.Em

Cite this article: 

Luo Xiao-Yuan (罗小元), Shao Shi-Kai (邵士凯), Zhang Yu-Yan (张玉燕), Li Shao-Bao (李绍宝), Guan Xin-Ping (关新平), Liu Zhi-Xin (刘志新) Generation of minimally persistent circle formation for a multi-agent system 2014 Chin. Phys. B 23 028901

[1] Yuan H and Qu Z 2009 IET Control Theory & Applications 3 712
[2] Cao M, Yu C B and Anderson B D O 2011 Automatica 47 776
[3] Olfati-Saber R 2006 IEEE Transactions on Automatic Control 51 401
[4] Kolling A and Carpin S 2010 IEEE Transactions on Robotics 26 32
[5] Dong W J 2011Journal of Intelligent & Robotic Systems 62 547
[6] Akyildiz I F, Su W, Sankarasubramaniam Y and Cayirci E 2002 IEEE Commun. Mag. 40 102
[7] Balch T and Arkin R C 1998 IEEE Transactions on Robotics and Automation 14 926
[8] Bender J G 1991 IEEE Transactions on Vehicualr Technology 40 82
[9] Swaroop D and Hedrick J K 1999 ASME Journal of Dynamic Systems, Measurement and Control 121 462
[10] Roth B 1981 American Mathematical Monthly 88 6
[11] Smith S, Egerstedt M and Howard A 2009 Mobile Networks and Applications 14 322
[12] Laman G 1970 J. Eng. Math. 4 331
[13] Fidan B, Yu C and Anderson B D O 2007 IET Control Theory & Applications 1 452
[14] Yu C, Hendrickx J M, Fidan B, Anderson B D O and Blondel V D 2007 Automatica 43 387
[15] Hendrickx J M, Fidan B, Yu C B, Anderson B D O and Blondel V D 2008 IEEE Trans. Autom. Control 53 968
[16] Luo X Y, Li S B and Guan X P 2009 Chin. Phys. B 18 3104
[17] Liu T F and Jiang Z P 2013 Automatica 49 592
[18] Cao M, Morse A S, Yu C, Anderson B D O and Dasgupta S 2011 Communication in Information and Systems 11 1
[19] Guo J, Lin Z, Cao M and Yan G 2010 in Proceedings of American Control Conference, Baltimore, USA, p. 6822
[20] Guo J, Yan G F and Lin Z Y 2010 Proceedings of IEEE International Conference on Robotics and Automation, May 3–8, 2010, Anchorage, USA, p. 1468
[21] Kawakami H and Namerikawa T 2008 IEEE International Conference on Control Applications, Sepember 3–5, 2008, San Antonio, USA, p. 1043
[22] Yan J, Luo X Y and Guan X P 2011 Chin. Phys. B 20 018901
[23] Yan J, Luo X Y and Guan X P 2011 Chin. Phys. B 20 048901
[24] Wu J and Shi Y 2011 Systems & Control Letters 60 863
[1] Distributed optimization for discrete-time multiagent systems with nonconvex control input constraints and switching topologies
Xiao-Yu Shen(沈小宇), Shuai Su(宿帅), and Hai-Liang Hou(侯海良). Chin. Phys. B, 2021, 30(12): 120507.
[2] Distance-based formation tracking control of multi-agent systems with double-integrator dynamics
Zixing Wu(吴梓杏), Jinsheng Sun(孙金生), Ximing Wang(王希铭). Chin. Phys. B, 2018, 27(6): 060202.
[3] Cooperative impulsive formation control for networked uncertain Euler-Lagrange systems with communication delays
Liang-ming Chen(陈亮名), Chuan-jiang Li(李传江), Yan-chao Sun(孙延超), Guang-fu Ma(马广富). Chin. Phys. B, 2017, 26(6): 068703.
[4] Rigidity based formation tracking for multi-agent networks
Bai Lu (白璐), Chen Fei (陈飞), Lan Wei-Yao (兰维瑶). Chin. Phys. B, 2015, 24(9): 090206.
[5] Distributed formation control for a multi-agent system with dynamic and static obstacle avoidances
Cao Jian-Fu (曹建福), Ling Zhi-Hao (凌志浩), Yuan Yi-Feng (袁宜峰), Gao Chong (高冲). Chin. Phys. B, 2014, 23(7): 070509.
[6] Leader-following formation control of multi-agent networks based on distributed observers
Luo Xiao-Yuan(罗小元),Han Na-Ni(韩娜妮), and Guan Xin-Ping(关新平). Chin. Phys. B, 2010, 19(10): 100202.
No Suggested Reading articles found!