[1]QIAN Dianwei.Formation control of multi-robot systems in a fuzzy sliding mode[J].CAAI Transactions on Intelligent Systems,2016,11(5):641-647.[doi:10.11992/tis.201510017]
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Formation control of multi-robot systems in a fuzzy sliding mode
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
11
Number of periods:
2016 5
Page number:
641-647
Column:
学术论文—智能系统
Public date:
2016-11-01
- Title:
- Formation control of multi-robot systems in a fuzzy sliding mode
- CLC:
- TP242.6
- DOI:
- 10.11992/tis.201510017
- Abstract:
- To resolve the formation problem resulting from a swarm of robots, a control scheme is proposed based on sliding mode control and fuzzy logic. A formation dynamic model is established utilizing the leader-follower approach. The model is subject to uncertainties. If the upper bounds of these uncertainties are unknown, then a fuzzy compensator can be adopted to approximate the uncertainties. From an Lyapunov approach, not only is the sliding-mode-based formation control system asymptotically stable, but the approximate error of the fuzzy compensator is also convergent. The simulation results demonstrate that the robots can rapidly form and maintain the desired specified geometrical shapes during movement.
- References:
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[1] HUDA M N, YU Hongnian, CANG Shuang. Behaviour-based control approach for the trajectory tracking of an underactuated planar capsule robot[J]. IET control theory & applications, 2015, 9(2):163-175.
[2] SADOWSKA A, VAN DEN BROEK T, HUIJBERTS H, et al. A virtual structure approach to formation control of unicycle mobile robots using mutual coupling[J]. International journal of control, 2011, 84(11):1886-1902.
[3] 杨丽, 曹志强, 谭民. 不确定环境下多机器人的动态编队控制[J]. 机器人, 2010, 32(2):283-288. YANG Li, CAO Zhiqiang, TAN Min. Dynamic formation control for multiple robots in uncertain environments[J]. Robot, 2010, 32(2):283-288.
[4] WANG Jinliang, WU Huaining. Leader-following formation control of multi-agent systems under fixed and switching topologies[J]. International journal of control, 2012, 85(6):695-705.
[5] 王奎民, 赵玉飞, 侯恕萍, 等. 一种改进人工势场的UUV动碍航物规避方法[J]. 智能系统学报, 2014, 9(1):47-52. WANG Kuimin, ZHAO Yufei, HOU Shuping, et al. Dynamic obstacle avoidance for unmanned underwater vehicle based on an improved artificial potential field[J]. CAAI transactions on intelligent systems, 2014, 9(1):47-52.
[6] ZHAO Weihua, GO T H. Quadcopter formation flight control combining MPC and robust feedback linearization[J]. Journal of the franklin institute, 2014, 351(3):1335-1355.
[7] GUILLET A, LENAIN R, THUILOT B, et al. Adaptable robot formation control:adaptive and predictive formation control of autonomous vehicles[J]. IEEE robotics & automation magazine, 2014, 21(1):28-39.
[8] LIU Hui, LI Junfeng. Terminal sliding mode control for spacecraft formation flying[J]. IEEE transactions on aerospace and electronic systems, 2009, 45(3):835-846.
[9] QIAN Dianwei, TONG Shiwen, GUO Jinrong, et al. Leader-follower-based formation control of nonholonomic mobile robots with mismatched uncertainties via integral sliding mode[J]. Proceedings of the institution of mechanical engineers, part I:journal of systems and control engineering, 2015, 229(6):559-569.
[10] 袁媛, 焦继乐, 曹志强, 等. 基于模糊控制协调策略的多自主机器人围捕[J]. 华中科技大学学报:自然科学版, 2011, 39(S2):328-331. YUAN Yuan, JIAO Jile, CAO Zhiqiang, et al. Fuzzy control coordination based hunting of multiple autonomous robots[J]. Journal of Huazhong university of science and technology:natural science edition, 2011, 39(S2):328-331.
[11] 王雪松, 高阳, 程玉虎, 等. 知识引导遗传算法实现机器人路径规划[J]. 控制与决策, 2009, 24(7):1043-1049. WANG Xuesong, GAO Yang, CHENG Yuhu, et al. Knowledge-guided genetic algorithm for path planning of robot[J]. Control and decision, 2009, 24(7):1043-1049.
[12] DEFOORT M, FLOQUET T, KOKOSY A, et al. Sliding-mode formation control for cooperative autonomous mobile robots[J]. IEEE transactions on industrial electronics, 2008, 55(11):3944-3953.
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1900-01-01