[1]YANG Mao,LI Cheng-feng,TIAN Yan-tao.Distributed coadaptive control and optimization ofswarm robot synchronization[J].CAAI Transactions on Intelligent Systems,2010,5(3):247-253.
Copy

Distributed coadaptive control and optimization ofswarm robot synchronization

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 3 Page number: 247-253 Column: 学术论文—智能系统 Public date: 2010-06-25
Title:
Distributed coadaptive control and optimization ofswarm robot synchronization
Author(s):
YANG Mao1;  LI Cheng-feng1;  TIAN Yan-tao1; 2
1. School of Communication Engineering, Jilin University, Changchun 130025, China;
2.Key Laboratory of Bionic Engineering (Jilin University), Ministry of Education, Changchun 130025, China
Keywords:
swarm robot;  synchronization;  cooperative control;  distributed controller;  PSO algorithms
CLC:
TP18
DOI:
-
Abstract:
Coadaptive control mechanisms for swarm robot systems were investigated to see if swarms could adapt to complex environments by using distributed control with local information exchange. The phenomenon of synchronization was studied, and on that basis a decentralized controller was proposed. It combined the ideas of a virtual force, the nearest neighborhood law, and environmental factors. It was proven that this controller can enable all swarm members to converge to a common velocity with bounded errors, whether the swarm topology is fixed or dynamic. The advantage of this controller is that it just needs local information to provide stable group behavior. In addition, parameters were optimized on the basis of the proposed controller to achieve the goal of minimum energy consumption. To deal with particle swarm optimization algorithms (PSO) easily falling into local optimums and having low accuracy, an improved algorithm was put forward. This was used to solve the energy optimization problem. Simulation results are included that verified the controller and algorithm.
References:
［1］胡中功，李静. 群智能算法的研究进展［J］.自动化技术与应用, 2008, 27(2): 1315.
?HU Zhonggong, LI Jing. The progress of swarm intelligence algorithms［J］.Techniques of Automation and Application,2008, 27(2): 1315.
［2］REYNOLDS C W. Flocks, birds, and schools: a distributed behavioral model［C］//Proceedings of ACM Computer Graphics (SIGGRAPH’87).New York, USA: ACM, 1987: 2534.
［3］VICSEK T, CZIROK A, BenJACOB E, COHEN I, SHOCHET O. Novel type of phase transition in a system of selfdriven particles［J］. Physical Reviews Letter, 1995, 75(6): 12261229.
［4］JADBABIE A, LIN J, MORSE A S. Coordination of groups of mobile autonomous agents using nearest neighborhood rules［J］. IEEE Transaction on Automatic Control, 2003, 48(6): 9881001.
［5］TANNER H G, JABABAIE A, PAPPAS G J. Flocking in fixed and switching networks［J］. IEEE Transaction on Automatic Control, 2007, 52(5): 863868.
［6］TANNER H G, JABABAIE A, PAPPAS G J. Stable flocking of mobile agent, part I: fixed topology［C］//Proceedings of Conference on Decision Control. Maui, HI, USA, 2003: 20102015.
［7］TANNER H G, JABABAIE A, PAPPAS G J. Stable flocking of mobile agent, part II: dynamic topology［C］//Proceedings of Conference on Decision Control. Maui, Hawaii, 2003: 20162021.
［8］GAZI V, PASSINO K M. Stability analysis of swarms［J］. IEEE Transaction on Automatic Control, 2003, 48: 692697.
［9］GAZI V, PASSINO K M. A class of attraction/repulsion functions for stable swarm aggregations［C］//Proceedings of Conference on Decision Control. Los Vegas, USA, 2002: 28422847.
［10］GAZI V, PASSINO K M. Stability analysis of swarms in an environment with an attractant/repellent profile［C］//Proceedings of American Control Conference. Anchorage, USA, 2002: 18191824.
［11］GAZI V, PASSINO K M. Stability analysis of social foraging swarms: combined effects of attractant/repellent profiles［C］//Proceedings of Conference on Decision Control. Las Vegas, USA, 2002: 114123.
［12］GAZI V, PASSINO K M. Stability analysis of social foraging swarm［J］. IEEE Transaction on Systems, Man, and CyberneticsPart B: Cybernetics, 2004, 34(1): 539557.
［13］LIU Yanfei, PASSINO K M. Stable social foraging swarms in a noisy environment［J］. IEEE Transaction on Automatic Control, 2004, 49(1): 3044.
［14］REIF J H, WANG Hongyan. Social potential fields: a distributed behavioral control for autonomous robots［J］. Robotics and Autonomous Systems, 1999, 27: 171194.
Similar References:

Memo

-

Last Update: 2010-08-27

Copyright © CAAI Transactions on Intelligent Systems