群集运动控制及其相关特性的研究
|
摘要
近年来，分布式大规模网络化群体系统的协调控制问题逐渐成为国内外智能系统理论界研究的热点。这源于自然界中广泛存在的群体现象，大规模群体系统不仅可以描述和解释大多数生物群体的群体协调行为和白组织现象，而且在工程上具有广阔的应用前景。因此，研究大规模群体系统的理论与应用具有重大的意义。
本论文在前人的研究基础上，对现有生物群体行为的涌现机制进行深入理解，研究分析群体系统群集行为以及与之相关的动态特性问题。
首先综述了大规模群体系统的发展历程，以及当前国内外关于群集行为建模与控制方法的理论研究和应用研究的现状。然后采用人工势能结合速度一致的策略，提出了一类带虚拟领航者的自适应的群集运动控制模型并分析了固定／切换两种拓扑结构下系统的稳定性，讨论了群体系统中局部外界环境和个体自身内部因素对群集行为的影响。
随后，在此基础上，将该问题推广到有障碍物空间，探讨了全局环境未知且存在静态障碍物的情况下群集运动控制与避障问题；并将个体扩展为具有记忆能力的智能个体，提出了一类基于记忆能力的大规模智能群体群集运动和避障控制策略，使群体能安全地穿过障碍区。
群体对应的拓扑结构为连通图是系统收敛必要条件；本文对连通性控制问题进行了深入研究，分析了连通性保持的实质；针对任意初始状态的群体系统提出了两种连通性控制策略；并采用相应的策略分别在系统对应的初始邻接图连通和不连通的两种条件下实现了连通性保持和群集运动控制，从而扩宽放松群集运动收敛的条件。
时延是网络系统中普遍存在的现象；本文以跟踪动态的领航者的群集现象为研究对象，研究分析了带时延的群集运动控制的稳定性问题。首先采用了时域和频域稳定性分析方法分析了固定时延和时变时延系统的稳定性，得出了带相同时延的群体系统收敛的条件。然后，采用频域法分析带多时延的群体系统的稳定性，该方法不要求时延的导数已知，从而放松拓宽了以往研究的限制条件；得出了系统按衰减度为α＞0的指数稳定的条件；并采用线性矩阵不等式方法(LMI)进一步探讨了带参数扰动的多时延的群集系统，得出了系统稳定运行的条件。最后，通过Lyapunov方法分析估计系统的跟踪误差，探讨了时延对系统性能(跟踪误差)的影响。
反馈机制是提高系统性能的有效方法；本文采用两种策略将反馈机制引入到有领航者的群集运动控制中，分析了该策略的鲁棒性以及容错性。模型中领航者按事先确定的轨迹运行，同时领航者需根据跟随者的状态信息自适应的调节自身的运行跟踪轨迹。研究分析表明该策略具有容错性，且减小了系统的跟踪误差，提高了系统的鲁棒性。
本文最后针对基于最小外接圆方法的群集模型的局限性，在前人的研究基础上，采用求解任意维空间点集的凸壳的方法，将该模型推广到n维空间中，对n维空间中群体的聚集以及迁徙行为进行建模和稳定性分析。
Recently, distributed coordination control of the scale networked swarm system has been a particularly active topic in intelligent system field. The effort has been inspired by common swarming phenomena existing in nature everywhere. The scale networked swarm system not only can describe and explain most of the coordinated behaviors and self-organization phenomena of biological swarms, but also has potential applications in engineering. Thus, it is signification to study the theory and applications of Large-scale swarm systems.
In this dissertation, through understanding the emergent mechanism of biological swarm, the further investigations on flocking control and the relevant dynamic characteristic of swarm behavior will be given.
Firstly, the history, the present status about the theory and applications research for swarm behavior are overviewed. Then, based on the strategy of combining artificial potential with velocity consensus, flocking control model based on virtual leaders which are chosen adaptively from the surrounding is built; the stability analysis for the fixed and switching swarm system are given; and the influence of local interior and exterior surrounding are discussed.
After that, we extend or combine existing methods to obstacle avoidance and flocking control in complex environments; then, we produce an intelligent swarm by giving individual agents some limited memories, and further discuss the obstacle avoidance and flocking control of the intelligent swarm. The result shows that the intelligent swarm can more efficient to achieve flocking motion in obstacle environment.
A common assumption in distributed coordination control problems is the connectedness of the underlying network. Further research is discussed in this dissertation. At first, we analyze the essential of connectivity maintenance. Then, two distributed control strategies for connectivity maintenance are proposed. At last, two kind of systems with arbitrary initial states are analyzed, i.e., connected system and disconnected system. Flocking motion with connectivity maintenance can be achieved for each of them. It is proved that flocking problem can be solved under a more relaxed condition.
Time-delay is ubiquitous in network system. For flocking behavior with an active leader, we discuss the stability of flocking motion with time delay. At first, we adopt a frequency-domain approach to this problem and discuss the stability of system with fixed time delay and time-varying delay. We derive sufficient conditions for the system under the same communication delays. Then, the stability of flocking motion with multiple time-delay is discussed with a frequency-domain approach that needs no derivative of time. A more relax convergence condition is obtained. Moreover, we further discuss the stability of uncertain systems with multiple time delays and perturbations by employing a linear matrix inequality method, and obtain the stability condition. At last tracing error is estimated by Lyapunov method, the time- delay influence on tracing error is discussed.
The strategy of information feedback is efficient to improve the performance of system. Two strategies of information feedback from followers to the leader are introduced to the flocking motion; the robustness and tolerance of the proposed method are studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion .The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers' faults.
At last, for the limition of the swarm model based on minimal circumcircle method, we extend the model to n-dimensional spaces; study the aggregating swarm behavior and flocking behavior; and analysis the stability of system.
本论文在前人的研究基础上，对现有生物群体行为的涌现机制进行深入理解，研究分析群体系统群集行为以及与之相关的动态特性问题。
首先综述了大规模群体系统的发展历程，以及当前国内外关于群集行为建模与控制方法的理论研究和应用研究的现状。然后采用人工势能结合速度一致的策略，提出了一类带虚拟领航者的自适应的群集运动控制模型并分析了固定／切换两种拓扑结构下系统的稳定性，讨论了群体系统中局部外界环境和个体自身内部因素对群集行为的影响。
随后，在此基础上，将该问题推广到有障碍物空间，探讨了全局环境未知且存在静态障碍物的情况下群集运动控制与避障问题；并将个体扩展为具有记忆能力的智能个体，提出了一类基于记忆能力的大规模智能群体群集运动和避障控制策略，使群体能安全地穿过障碍区。
群体对应的拓扑结构为连通图是系统收敛必要条件；本文对连通性控制问题进行了深入研究，分析了连通性保持的实质；针对任意初始状态的群体系统提出了两种连通性控制策略；并采用相应的策略分别在系统对应的初始邻接图连通和不连通的两种条件下实现了连通性保持和群集运动控制，从而扩宽放松群集运动收敛的条件。
时延是网络系统中普遍存在的现象；本文以跟踪动态的领航者的群集现象为研究对象，研究分析了带时延的群集运动控制的稳定性问题。首先采用了时域和频域稳定性分析方法分析了固定时延和时变时延系统的稳定性，得出了带相同时延的群体系统收敛的条件。然后，采用频域法分析带多时延的群体系统的稳定性，该方法不要求时延的导数已知，从而放松拓宽了以往研究的限制条件；得出了系统按衰减度为α＞0的指数稳定的条件；并采用线性矩阵不等式方法(LMI)进一步探讨了带参数扰动的多时延的群集系统，得出了系统稳定运行的条件。最后，通过Lyapunov方法分析估计系统的跟踪误差，探讨了时延对系统性能(跟踪误差)的影响。
反馈机制是提高系统性能的有效方法；本文采用两种策略将反馈机制引入到有领航者的群集运动控制中，分析了该策略的鲁棒性以及容错性。模型中领航者按事先确定的轨迹运行，同时领航者需根据跟随者的状态信息自适应的调节自身的运行跟踪轨迹。研究分析表明该策略具有容错性，且减小了系统的跟踪误差，提高了系统的鲁棒性。
本文最后针对基于最小外接圆方法的群集模型的局限性，在前人的研究基础上，采用求解任意维空间点集的凸壳的方法，将该模型推广到n维空间中，对n维空间中群体的聚集以及迁徙行为进行建模和稳定性分析。
Recently, distributed coordination control of the scale networked swarm system has been a particularly active topic in intelligent system field. The effort has been inspired by common swarming phenomena existing in nature everywhere. The scale networked swarm system not only can describe and explain most of the coordinated behaviors and self-organization phenomena of biological swarms, but also has potential applications in engineering. Thus, it is signification to study the theory and applications of Large-scale swarm systems.
In this dissertation, through understanding the emergent mechanism of biological swarm, the further investigations on flocking control and the relevant dynamic characteristic of swarm behavior will be given.
Firstly, the history, the present status about the theory and applications research for swarm behavior are overviewed. Then, based on the strategy of combining artificial potential with velocity consensus, flocking control model based on virtual leaders which are chosen adaptively from the surrounding is built; the stability analysis for the fixed and switching swarm system are given; and the influence of local interior and exterior surrounding are discussed.
After that, we extend or combine existing methods to obstacle avoidance and flocking control in complex environments; then, we produce an intelligent swarm by giving individual agents some limited memories, and further discuss the obstacle avoidance and flocking control of the intelligent swarm. The result shows that the intelligent swarm can more efficient to achieve flocking motion in obstacle environment.
A common assumption in distributed coordination control problems is the connectedness of the underlying network. Further research is discussed in this dissertation. At first, we analyze the essential of connectivity maintenance. Then, two distributed control strategies for connectivity maintenance are proposed. At last, two kind of systems with arbitrary initial states are analyzed, i.e., connected system and disconnected system. Flocking motion with connectivity maintenance can be achieved for each of them. It is proved that flocking problem can be solved under a more relaxed condition.
Time-delay is ubiquitous in network system. For flocking behavior with an active leader, we discuss the stability of flocking motion with time delay. At first, we adopt a frequency-domain approach to this problem and discuss the stability of system with fixed time delay and time-varying delay. We derive sufficient conditions for the system under the same communication delays. Then, the stability of flocking motion with multiple time-delay is discussed with a frequency-domain approach that needs no derivative of time. A more relax convergence condition is obtained. Moreover, we further discuss the stability of uncertain systems with multiple time delays and perturbations by employing a linear matrix inequality method, and obtain the stability condition. At last tracing error is estimated by Lyapunov method, the time- delay influence on tracing error is discussed.
The strategy of information feedback is efficient to improve the performance of system. Two strategies of information feedback from followers to the leader are introduced to the flocking motion; the robustness and tolerance of the proposed method are studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion .The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers' faults.
At last, for the limition of the swarm model based on minimal circumcircle method, we extend the model to n-dimensional spaces; study the aggregating swarm behavior and flocking behavior; and analysis the stability of system.
引文
[1]E. Ben-Jacob, I. Cohen and H. Levine, Cooperative self-organization of microorganisms, Advances In Physics, 2000, 49(4): 395-554
[2]K M. Passino, Biomimicry of bacterial foraging for distributed optimization and control.IEEE Control Systems Magazine, 2002,22(3):52-67.
[3]R C. Eberhart and J. Kenedy, Swarm Intelligence, San Francisco:Morgan Kaufmann.2001.
[4]S.Camazine, J L.Deneubourg and N R Franks,Self-Organization in Biological Systems.Princeton, NJ:Princeton University Press.2003.
[5]程代展，陈翰馥，从群集到社会行为控制，复杂性科学研究专题，科技导报，2004，8： 4-7
[6]齐欢，王小平，系统建模与仿真，北京：清华大学出版社(第1版)，2004．
[7]C. Reynolds, Flocks, birds, and schools: a distributed behavioral model, Computer Graphics, 1987, 21(4): 25-34
[8]D. Morale, Modeling and simulating animal grouping individual-based models, Future Generation Computer Systems, 2001, 17: 883-891.
[9]陈森发，复杂系统建模理论与方法，东南大学出版社(第1版)，南京：宋增民，2005，3-4
[10]C. M, Breder, Equations Descriptive of Fish Schools and Other Animal Aggregations,Ecology, 1954,35(3):361-370.
[11]D. Grunbaum, Local processes and global patterns: biomathematical models of bryozoan feeding currents and density dependent aggregations in Antarctic krill. Ph. D. thesis, Cornell University, Ithaca, NY, 1992
[12]D. Grunbaum, Schooling as a strategy for taxis in a noisy environment, Evolutionary Ecology, 1998,12(5):503-522.
[13]D. Grunbaum, Translating stochastic density-dependent individual behavior with sensory constraints to an Eulerian model of animal swarming. Journal of Mathematical Biology, 1994, 33:139-161
[14]A. Mogilner and L. Edelstein-Keshet, A non-local model for a swarm, Journal of Mathematical Biology, 1999, 38(6): 534-570
[15]P. Grindrod, Models of individual aggregation or clustering in single and multi-species communities, Journal of Mathematical Biology, 1988, 26:651-660
[16]T. Vicsek, A. Czirok and E. Ben Jacob et al, Novel type of phase transitions in a system of self-driven particles, Physical Review Letters, 1995, 75: 1226-1229
[17]K. Warburton and J. Lazarus, Tendency-distance models of social cohesion in animal groups, Journal of Theoretical Biology, 1991, 150:473-488
[18]K. Jin, P. Liang and G. Beni, stability of synchronized distributed control of discrete swarm structures, Proceedings of IEEE International conference on robotics and automation, San Diego, 1994, 1033-1038
[19]G. Beni and P. Liang, pattern reconfiguration in swarms convergence of a distributed asynchronous and bounded iterative algorithm, IEEE Transaction on Robotics and Automation, 1996, 12:485-490
[20]V. Gazi and K. M. Passino, Stability analysis of swarms, IEEE Transaction on Aut- omatic Control, 2003, 48: 692-697.
[21]V. Gazi and K. M. Passino, A class of attraction/repulsion function for stable swarm aggregation, Proceedings of the 41st IEEE Conference on Decision and Control, Las Vegas, Nevada USA, 2002, 2842-2847
[22]Yianguang Chu, Long Wang and T Chen, Self-organized motion in anisotropic swarms, Journal of Control Theory and Applications, 2003, 1 (1): 77-81
[23]Tianguang Chu, Long Wang and Shumei Mu, Collective behavior analysis of an anisotropic swarm model, The 16th International Symposium on Mathematical Theory of Network and Systems, Leuven, Belgium, 2004, 1-13
[24]Hong Shi, Long Wang and Tianguang Chu, Swarming behavior of multi-agent systems, Journal of Control Theory and Applications, 2004, 4:313-318
[25]B. Liu, Tianguang Chu and Long Wang et al., Swarm dynamics of a group of mobile autonomous agents. Chinese Physics Letters, 2005, 22(1): 254-257
[26]陈世明，方华京，大规模智能群体的建模及稳定性分析，控制与决策，2005，20 (5)：490-494．
[27]Shiming Chen and Huajing Fang, Modeling and Stability Analysis of Emergent Behavior of Scalable Swarm System,The International Journal of Zhejiang University SCIENCE,2006,7 (6) :952-959.
[28]陈世明，方华京，大规模移动智能群体的建模及联合行为分析，控制与决策，2005，20(12)：1392-1396．
[29]Shiming Chen and Huajing Fang, An improved cooperative tracking model used for large scale foraging swarm, ACTA Automatica tica SINICA, 2006,32(1):38-42.
[30]C. Topaz and A. Bertozzi, Swarming patterns in a two dimensional kinematic model for biological groups,SIAM Journal of Application Mathematic. 2004, 65 (1): 152-174
[31]A. Jadbabaie, J. Lin and A. S. Morse, coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Transactions on Automatic Control, 2003, 48(6):988-1001
[32]A. Jadbabaie, On coordination strategies for mobile agents with changing nearest neighbor sets, IEEE Mediterranian Conference on Control and Automation, Rhodes, Greece, 2003,7.
[33]S. Li and H. Wang, Multi-agent coordination using nearest neighbor rules: Revisiting the Vicsek model, http://arxiv.org/abs/cs/0407021
[34]R. O. Saber r and R. M. Murray, Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control, 2004, 49(9): 1520-1533.
[35]R. O. Saber and R. M. Murray, Agreement problems in networks with directed graphs and switching topology.Proceedings of IEEE Conference on Decision and Control, 2003: 4126-4132.
[36]R. O. Saber and R. M. Murray, Consensus protocols for networks of dynamic agents, Proceedings of the American Control Conference, 2003:951-956.
[37]W. Ren and R. W. Beard, Consensus seeking in multi-agent systems under dynamically changing interaction topologies, IEEE Trans. Autom. Control, 2005,50( 5): 655-661.
[38]俞辉，蹇继贵，王永骥，多智能体时滞网络的加权平均一致性，控制与决策， 2007,22(5):558-561
[39]俞辉，蹇继贵，多智能体有向切换网络的加权平均一致性，27届中国控制会议论文集，2008：526-530．
[40]L. Moreau, Stability of continuous-time distributed consensus algorithms, Decision and Control, 2004. CDC. 43rd IEEE Conference, 2004, 4: 3998-4003.
[41]Z. Lin, M Broucke,B Francis,Local control strategies for groups of mobile autonomous agents.IEEE Transactions on Automatic Control, 2004, 49 (4): 622-629.
[42]L.Xiao and S Boyd, Fast linear iterations for distributed averaging. Systems and Control Letters, 2004, 53 (1): 65-78.
[43]Wei Li and Xiaofan Wang, Adaptive velocity strategy for swarm aggregation. Phys. Rev. E,2007, 75(2): 021917-1-021917-8
[44]W. Ren, R. W. Beard and E. M. Atkins,A survey of consensus problems in multi-agent Coordination. American Control Conference, Portland, OR, 2005: 1859-1864.
[45]Wen Yang, Xiao fan Wang and Xiang Li, A Survey of Consensus Problem in Multi-Agent Systems, Control Conference Chinese, 2006:1491-1495
[46]R.O. Saber, J. A. Fax, and R. M. Murray, Consensus and cooperation in networked multi-agent systems, Proceedings IEEE, 95 (1): 215-233.
[47]W. Ren,On Consensus Algorithms for Double-integrator Dynamics, IEEE Transactions on Automatic Control, 2008,53(6): 1503-1509
[48]G. Xie and L. Wang, Consensus Control for a class of Networks of Dynamic Agents:Fixed Topolog, IEEE Conference on Decision and Control, 2005:96-101.
[49]G. Xie and L. Wang, Consensus Control for a class of Networks of Dynamic Agents: switching Topology, in Proc. of ACC, June 2006, pp. 1382-1387.
[50]林鹏 贾英民， 二阶动态智能体网络的一致性控制， http://www.paper.edu.cn/debug/downloadpaper.php?serial_number=200611-847&ty pe=l
[51]D.V. Dimarogonas and K.J. Kyriakopoulos, Connectivity preserving distributed swarm aggregation for multiple kinematic agents,46th IEEE Conf. Decision and Control, 2007:2913-2918.
[52] D.V. Dimarogonas and K.J. Kyriakopoulos, Connectivity Preserving State Agreement for Multiple Unicycles. American Control Conference, 2007,1179-1184
[53] M. M. Zavlanos and G. J. Pappas,Potential Fields for Maintaining Connectivity of Mobile Networks IEEE Transactions on Robotics, 2007(23)4:1-4
[54] M. M. Zavlanos and G. J. Pappas, Controlling connectivity of dynamic graphs, IEEE Conference on Decision and Control, 2005:6388-6393.
[55] M. M. Zavlanos, A. Jadbabaie, G. J. Pappas, Flocking while preserving network connectivity. Proc.of the IEEE Conference on Decision and Control, 2007:2919-2924.
[56] D.V. Dimarogonas and K.J Kyriakopoulos, Decentralized connectivity maintenance in mobile networks with bounded inputs, IEEE Conference on Robotics and Automation, Pasadena, CA, 2008:1507-1712
[57] M.C. De Gennaro and A. Jadbabaie, Decentralized control of connectivity for multi-agent systems. 45th IEEE Conference Decision and Control,2006: 3628-3633.
[58] M. Ji and M. Egerstedt.Connectedness preserving distibuted coordination control over dynamic graphs, American Control Conference, 2005: 93-98.
[59] M. Ji and M. Egerstedt.Distributed coordination control of multi-agent systems while preserving connectedness.IEEE Transactions on Robotics, 2007,23(4): 693 -703.
[60] W Wang, and J E Slotine, Contraction analysis of time-delayed communications and group cooperation. IEEE Trans on Automatic Control, 2006, 51 (4): 712-717.
[61] P. A. Bliman andG. Ferrari Trecate, Average consensus problems in networks of agents with delayed communications. Proceeding of the 44th IEEE Conference on Decision and Control, and the European Control Conference. Spain:Seville, 2005:7066-7071.
[62] 刘成林,田玉平,具有不同通信时延的多个体系统的一致性,东南大学学报,2008,38(1):170-174.
[63] Yuan Gong Sun, LongWang and Guangming Xie. Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays,Systems & Control Letters,2008,57:175-183
[64] Yuan Gong Sun, LongWang and Guangming Xie.Average Consensus in Directed Networks of Dynamic Agents with Time-Varying Communication Delays,45th IEEE Conference on Decision Control, San Diego, CA, USA, 2006:3393-3398
[65] P. Lin, Y. Jia, J. Du, and S. Yuan, Distributed consensus control for networks of second-order agents with fixed topology and time-delay. Proceedings of the 26th Chinese Control Conference, 2007:577-581.
[66] P. Lin and Y. Jia, Distributed robust H_∞ consensus control in directed networks of agents with time-delay, Systems and Control Letters, 2008,(57)8:643-653
[67] P. Lin and Y. Jia, Average-consensus in networks of multi-agents with both switching topology and coupling time-delay, Physica A, 2008,(387)1:303-313.
[68] Cheng Lin Liu and Yu Ping Tian, Coordination of Multi-agent Systems with Time-Varying Delays, Proceedings of the 27th Chinese Control Conference,Kunming 2008:76-80
[69] Cheng Lin Liu and Yu Ping Tian, Coordination of multi-agent system with communication delays. The International Federation of Automatic Control Seoul, Korea, July 6-11,2008:10782-10787
[70] J. Hu, Y. Hong, Leader-following coordination of multi-agent systems with coupling time delays. Physica A .2007: 853-863.
[71] H. G. Tanner, A. Jadbabaie, and G. J. Pappas, Stable flocking of mobile agents, part i: Fixed topology, in Proc. of CDC, (Maui, Hawaii), 2003: 2010-2015.
[72] H. G. Tanner, A. Jadbabaie, and G. J. Pappas, Stable flocking of mobile agents, part ii: Dynamic topology,in Proc. of CDC, (Maui, Hawaii), 2003: 2016-2021.
[73] R. O. Saber, A unified analytical look at Reynolds flocking rules, Technical Report 2003-014, California Institute of Technology, Control and Dynamical Systems,Pasadena, California, 2003
[74] N. E. Leonard and E. Fiorelli, Virtual leaders, artificial potentials and coordinated control of groups, in Proc. IEEE Conference on Decision and Control, Orlando,Florida USA, 2001, 3:2968-2973.
[75] R. O. Saber, Flocking for multi-agent dynamic systems: Algorithms and theory,IEEE Transactions on Automatic Control,2006,51(3):401-420.
[76] Long Wang, Hong Shi and Tianguang Chu, Flocking control of groups of mobile autonomous agents via local feedback, Proc of the 2005 IEEE International Symposium on Intelligent Control, Limassol, Cyprus, 2005:441-446.
[77] Hui Yu and Yongji Wang, Control of stable flocking motion of multi-agent with a leader, Journal of Huazhong University of Science and Technology (Nature Science Edition), 2005, 33(8): 56-58.
[78] Hui Yu and Yongji Wang,Stable flocking motion of mobile agents following a leader infixed and switching networks,International Journal of Automation and Computing, 2006,3(1):8-16
[79] Y. Liu, K. M. Passino, and M. Polycarpou, Stability analysis of m-dimensional asynchronous swarms with a fixed communication topology, IEEE Transactions on Automatic Control, 2003,48(1): 76-95.
[80] Housheng Su,Xiaofan Wang and Zongli Lin, Flocking of Multi-Agents with a Virtual Leader Part?: with a Minority of Informed Agents, 46th IEEE Conference on Decision and Control, New Orleans, LA, USA,2007: 12-14.
[81] Housheng Su,Xiaofan Wang and Zongli Lin, Flocking of Multi-Agents with a Virtual Leader Part ?: with a Virtual Leader of Varying Velocity,46th IEEE Conference on Decision and Control, New Orleans, LA, USA,2007: 12-14.
[82] R. O. Saber and R.M.Murray Flocking with Obstacle Avoidance: Cooperations with Limited Communication in Mobile Networks, IEEE Conference on Decision and Control, 2003,(2): 2022-2028
[83] R. O. Saber,Flocking with Obstacle Avoidance,Technical Report 2003-006,California Institute of Technology, Control and Dynamical Systems, Pasadena,California, February 2003,http://resolver.caltech.edu/CaltechCDSTR:2003.006.
[84] H. G. Tanner, Flocking with Obstacle Avoidance in Switching Networks of Interconnected Vehicles. IEEE International Conference Robotics and Automation,New Orleans LA, 2004:3006-3011.
[85] E. Rimon and D. Koditschek, Exact Robot Navigation Using Artificial Potential Functions.IEEE Transactions on Robotics and Automation. 1992, 8(5): 501-518.
[86] M Lindhe, P (?)gren and .K. H. Johansson ,Flocking with obstacle avoidance: A new distributed coordination algorithm based on Voronoi partitions, Robotics and Automation, Barcelona, Spain 2005: 1785-1790
[87]Yan fei Liu and K. M. Passino, Stable social foraging swarms in a noisy environment, IEEE Transaction on Automatic Control, 2004, 49(1): 30-44
[88]V. Gazi and K. M. Passino, Stability analysis of social foraging swarms, IEEE Transactions on Systems, Man, and Cybernetics -part B: Cybernetics, 2004,34(1): 539-556
[89]X. Li, J. Xiao, and Z. Cai, Stable flocking of swarms using local information, in Conference Proceedings IEEE International Conference on Systems, Man and Cybernetics, 2005, 3921-3926
[90]J. H. Reif and H. Wang, social potential fields: a distributed behavioral control for autonomous robots, Robotics and Autonomous Systems, 1999,27:171-194
[91]T. Balch and R. C. Arkin, Behavior-based formation control for multi-robot teams, IEEE Transaction on Robotics and Automation, 1998, 14(6): 926-939
[92]M.Schneider-Fontan, M.J Mataric, Territorial multi-robot task division, IEEE Trans. Robot, Autom, 1998, 14, 815-822
[93]J.R. Lawton, B. J. Young and R. W. Beard, A decentralized approach to elementary formation maneuvers, In: Proceeding of IEEE International Conference on Robotics and Automation, San Francisco, CA, 2000, 3:2728-2733
[94]J.R. Lawton, R.W.Beard, Synchronized multiple spacecraft rotations, Automatica, 2000, 38, (8), pp. 1359-1364
[95]Damian Dobroczynski, Multi-agent behavioral control system for a group of mobile robots, Second Workshop on Robot Motion and Control, 2001, 18-20
[96]苏治宝，陆际联，基于行为法队形保持中的队形反馈，机床与液压，2003，3： 167-169
[97]P.K.C. Wang. Navigation strategies for multiple autonomous mobile robots moving in formation, Journal of.Robot and System, 1991, 8(2): 177-195
[98]T. Sugar, V. Kumar, Decentralized control of cooperating mobile manipulators, Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium, May 1998, 2916-2921
[99]J.P. Desai, J. Ostrowski and V. Kumar.Controlling formations of multiple mobile robots, In: Proceeding of IEEE International Conference of Robot and Automation, Leuven, Belgium. 1998, 2864-2869
[100]H. Yamaguchi, J. W. Burdick. Asymptotic stabilization of multiple nonholonomic mobile robots forming group formations,Proceedings of IEEE International Conference on Robotics and Automation, Leuven, Belgium, 1998,3573-3580
[101]M.Mesbahi, F.Y. Hadaegh, Formation flying control of multiple spacecraft via graphs, matrix inequalities, and switching, J. Guid.Control Dyn., 2000, 24, 369-377
[102]R. W. Beard, J. Lawton and F. Y. Hadaegh, A coordination architecture for spacecraft formation control, IEEE Transaction on Control Systems Technology, 2000, 9(6): 777-790
[103]W.Ren, R. W. Beard, A decentralized scheme for spacecraft formation flying via virtual structure approach, Proceedings of the American Control Conference, Denver, Colorado, American Automatic Control Council, 2003: 1746-1751
[104]B. J. Young, R. W. Beard and J. M. Kelsey, A control scheme for improving multi-vehicle formation maneuvers, In: Proceeding of the American Control Conference, Arlington, VA, 2001, 2:704-709
[105]景兴建，王越超，谈大龙，基于人工协调场的多移动机器人实时协调避碰规划，控制理论与应用，2004，21(5)：757-764
[106]D. E. Koditschek, An approach to autonomous robot assembly, Robotica, 1994,12: 137-155
[107]H. Yamaguchi, Adaptive formation control for distributed autonomous mobile robot groups, In: Proceeding of the IEEE. International Conference on Robotics and Automation, Albuquerque, New Mexico, 1997, 3:2300-2305
[108]E. Rimon and D. E. Koditschek, exact robot navigation using artificial potential functions, IEEE Transaction on Robotics and Automation, 1992, 8(5): 501-518
[109]J. Finke, K. M ,Passino and S Ganapathy, Cooperative control via task load balancing for networked uninhabited autonomous vehicles, 42nd IEEE Conference on Decision and Control,Hawaii, 2003:31-36
[110]A,GilL,S Ganapathy and K. M ,Passino, Cooperative scheduling of tasks for networked autonomous vehicles, 42nd IEEE Conference on Decision and Control, Hawaii, 2003:522-527
[111]Y Liu and K. M Passino, Biomimicry of social foraging bacteria for distributed optimization: models, principles and emergent behaviors, Journal of Optimization Theory and Applications, 2002,115(3):603-628.
[112]K. M Passino, Biomimicry of bacterial foraging for distributed optimization and control, IEEE Control Systems Magazine,2002,22(3):52-67.
[113]V. Gazi, Swarm aggregations using artificial potentials and sliding mode control, IEEE Transactions on Robotics,2005,21 (6): 1208-1214.
[114]A. F. Filippov, Differential equations with discontinuous right-hand side. Mathematics and Its Applications (Soviet Series), Kluwer Academic Publishers, The Netherlands, 1988.
[ll5]H.Frank,Clarke,Optimization and Nonsmooth Analysis Classics in applied mathematics, 5.SIAM, Philadelphia, 1990.
[116]I. D Couzin, J .Krause and R.Jamesetl, Collective memory and spatial sorting in animal groups.Journal of Theoretical Biology, 2002, 218:1-11.
[117]高云园，韦巍．未知环境中基于免疫网络的多机器人自主协作．浙江大学学报(工学版)，2006,40(5)：733-737
[118]R.Winder, J. Reggia, Distributed partial Memories to Improve Self-Organizing collective movements.IEEE Trans. SMC B. 2004, 34:1967-1707.
[119]Alejandro Rodriguez and James A. Reggia, Extending self-organizing particle systems to problem solving.Artificial Life. 2004, 10 (4):379-395
[121]张纯刚，席裕庚．全局环境未知时基于滚动窗口的机器人路径规划．中国科学(E)辑，2001．31(2)51-58．
[122]李少逸，董慧颖，陈文波，基于Limit-cycle的机器人动态路径规划方法．沈阳工学院学报，2004，(23)1：50-53
[123]D. H. Kim, J. H. Kim, A real-time limit-cycle navigation method for fast mobile robot and its application to robot soccer.Robotics and Autonomous Systems, 2003,42( 1 ): 17-30.
[124]程拥强，蒋平，朱劲，郭凤龙，用势场法改进的极限环导航方法在移动机器人中的应用，机器人，2004,26(2)：133-138
[125] R. W. Beard, J. Lawton and F. Y. Hadaegh, A feedback architecture for formation control, in Proc. American Control Conference, June 28-30, 2000(6): 4087-4091.
[126] W.Ren, and R.W Beard, Virtual structure based spacecraft formation control with formation feedback. Presented at AIAA Guidance, Navigation, and Control Conf.,Monterey, CA, August 2002
[127] F. Zhang, W. Chen and Y. Xi, Motion synchronization of mobile robot networks:robustness, in Proc. of IEEE/RSJ Conf. on Intelligent Robots and Systems (IROS),Beijing, China, Oct. 2006:5570-5575.
[128] X. F. Wang and G. Chen, Synchronization in scale-free dynamical networks:Robustness and fragility, IEEE Trans. on Circ. and Syst.-I, 2002,(49)1: 54-62.
[129] B. Boyd, L.E. Ghaoui, E. Feron, V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, SIAM, Philadelphia, PA, 1994.
[130] Xi Li ,De Souza and Carlos E. Criteria for robust stability and stabilization of uncertain linear systems with state delay Automatica ,1997 ,33 (9) :1657-1662.
[131]Zili Li and Zengqiang Chen,A Criterion of the Consensus Problems in Multi-agent Systems with One Leader and Multi-follower. Proceedings of the 27th Chinese Control Conference, Kunming, China,2008,536-539.
[132] Feng Guo, Xizhao Wang and Yan Li, A new algorithm for solving convex hull problem and its application to feature selection, International conference on Machine learning and cybernetics, Kunming, 2008,369-373.
[2]K M. Passino, Biomimicry of bacterial foraging for distributed optimization and control.IEEE Control Systems Magazine, 2002,22(3):52-67.
[3]R C. Eberhart and J. Kenedy, Swarm Intelligence, San Francisco:Morgan Kaufmann.2001.
[4]S.Camazine, J L.Deneubourg and N R Franks,Self-Organization in Biological Systems.Princeton, NJ:Princeton University Press.2003.
[5]程代展，陈翰馥，从群集到社会行为控制，复杂性科学研究专题，科技导报，2004，8： 4-7
[6]齐欢，王小平，系统建模与仿真，北京：清华大学出版社(第1版)，2004．
[7]C. Reynolds, Flocks, birds, and schools: a distributed behavioral model, Computer Graphics, 1987, 21(4): 25-34
[8]D. Morale, Modeling and simulating animal grouping individual-based models, Future Generation Computer Systems, 2001, 17: 883-891.
[9]陈森发，复杂系统建模理论与方法，东南大学出版社(第1版)，南京：宋增民，2005，3-4
[10]C. M, Breder, Equations Descriptive of Fish Schools and Other Animal Aggregations,Ecology, 1954,35(3):361-370.
[11]D. Grunbaum, Local processes and global patterns: biomathematical models of bryozoan feeding currents and density dependent aggregations in Antarctic krill. Ph. D. thesis, Cornell University, Ithaca, NY, 1992
[12]D. Grunbaum, Schooling as a strategy for taxis in a noisy environment, Evolutionary Ecology, 1998,12(5):503-522.
[13]D. Grunbaum, Translating stochastic density-dependent individual behavior with sensory constraints to an Eulerian model of animal swarming. Journal of Mathematical Biology, 1994, 33:139-161
[14]A. Mogilner and L. Edelstein-Keshet, A non-local model for a swarm, Journal of Mathematical Biology, 1999, 38(6): 534-570
[15]P. Grindrod, Models of individual aggregation or clustering in single and multi-species communities, Journal of Mathematical Biology, 1988, 26:651-660
[16]T. Vicsek, A. Czirok and E. Ben Jacob et al, Novel type of phase transitions in a system of self-driven particles, Physical Review Letters, 1995, 75: 1226-1229
[17]K. Warburton and J. Lazarus, Tendency-distance models of social cohesion in animal groups, Journal of Theoretical Biology, 1991, 150:473-488
[18]K. Jin, P. Liang and G. Beni, stability of synchronized distributed control of discrete swarm structures, Proceedings of IEEE International conference on robotics and automation, San Diego, 1994, 1033-1038
[19]G. Beni and P. Liang, pattern reconfiguration in swarms convergence of a distributed asynchronous and bounded iterative algorithm, IEEE Transaction on Robotics and Automation, 1996, 12:485-490
[20]V. Gazi and K. M. Passino, Stability analysis of swarms, IEEE Transaction on Aut- omatic Control, 2003, 48: 692-697.
[21]V. Gazi and K. M. Passino, A class of attraction/repulsion function for stable swarm aggregation, Proceedings of the 41st IEEE Conference on Decision and Control, Las Vegas, Nevada USA, 2002, 2842-2847
[22]Yianguang Chu, Long Wang and T Chen, Self-organized motion in anisotropic swarms, Journal of Control Theory and Applications, 2003, 1 (1): 77-81
[23]Tianguang Chu, Long Wang and Shumei Mu, Collective behavior analysis of an anisotropic swarm model, The 16th International Symposium on Mathematical Theory of Network and Systems, Leuven, Belgium, 2004, 1-13
[24]Hong Shi, Long Wang and Tianguang Chu, Swarming behavior of multi-agent systems, Journal of Control Theory and Applications, 2004, 4:313-318
[25]B. Liu, Tianguang Chu and Long Wang et al., Swarm dynamics of a group of mobile autonomous agents. Chinese Physics Letters, 2005, 22(1): 254-257
[26]陈世明，方华京，大规模智能群体的建模及稳定性分析，控制与决策，2005，20 (5)：490-494．
[27]Shiming Chen and Huajing Fang, Modeling and Stability Analysis of Emergent Behavior of Scalable Swarm System,The International Journal of Zhejiang University SCIENCE,2006,7 (6) :952-959.
[28]陈世明，方华京，大规模移动智能群体的建模及联合行为分析，控制与决策，2005，20(12)：1392-1396．
[29]Shiming Chen and Huajing Fang, An improved cooperative tracking model used for large scale foraging swarm, ACTA Automatica tica SINICA, 2006,32(1):38-42.
[30]C. Topaz and A. Bertozzi, Swarming patterns in a two dimensional kinematic model for biological groups,SIAM Journal of Application Mathematic. 2004, 65 (1): 152-174
[31]A. Jadbabaie, J. Lin and A. S. Morse, coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Transactions on Automatic Control, 2003, 48(6):988-1001
[32]A. Jadbabaie, On coordination strategies for mobile agents with changing nearest neighbor sets, IEEE Mediterranian Conference on Control and Automation, Rhodes, Greece, 2003,7.
[33]S. Li and H. Wang, Multi-agent coordination using nearest neighbor rules: Revisiting the Vicsek model, http://arxiv.org/abs/cs/0407021
[34]R. O. Saber r and R. M. Murray, Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control, 2004, 49(9): 1520-1533.
[35]R. O. Saber and R. M. Murray, Agreement problems in networks with directed graphs and switching topology.Proceedings of IEEE Conference on Decision and Control, 2003: 4126-4132.
[36]R. O. Saber and R. M. Murray, Consensus protocols for networks of dynamic agents, Proceedings of the American Control Conference, 2003:951-956.
[37]W. Ren and R. W. Beard, Consensus seeking in multi-agent systems under dynamically changing interaction topologies, IEEE Trans. Autom. Control, 2005,50( 5): 655-661.
[38]俞辉，蹇继贵，王永骥，多智能体时滞网络的加权平均一致性，控制与决策， 2007,22(5):558-561
[39]俞辉，蹇继贵，多智能体有向切换网络的加权平均一致性，27届中国控制会议论文集，2008：526-530．
[40]L. Moreau, Stability of continuous-time distributed consensus algorithms, Decision and Control, 2004. CDC. 43rd IEEE Conference, 2004, 4: 3998-4003.
[41]Z. Lin, M Broucke,B Francis,Local control strategies for groups of mobile autonomous agents.IEEE Transactions on Automatic Control, 2004, 49 (4): 622-629.
[42]L.Xiao and S Boyd, Fast linear iterations for distributed averaging. Systems and Control Letters, 2004, 53 (1): 65-78.
[43]Wei Li and Xiaofan Wang, Adaptive velocity strategy for swarm aggregation. Phys. Rev. E,2007, 75(2): 021917-1-021917-8
[44]W. Ren, R. W. Beard and E. M. Atkins,A survey of consensus problems in multi-agent Coordination. American Control Conference, Portland, OR, 2005: 1859-1864.
[45]Wen Yang, Xiao fan Wang and Xiang Li, A Survey of Consensus Problem in Multi-Agent Systems, Control Conference Chinese, 2006:1491-1495
[46]R.O. Saber, J. A. Fax, and R. M. Murray, Consensus and cooperation in networked multi-agent systems, Proceedings IEEE, 95 (1): 215-233.
[47]W. Ren,On Consensus Algorithms for Double-integrator Dynamics, IEEE Transactions on Automatic Control, 2008,53(6): 1503-1509
[48]G. Xie and L. Wang, Consensus Control for a class of Networks of Dynamic Agents:Fixed Topolog, IEEE Conference on Decision and Control, 2005:96-101.
[49]G. Xie and L. Wang, Consensus Control for a class of Networks of Dynamic Agents: switching Topology, in Proc. of ACC, June 2006, pp. 1382-1387.
[50]林鹏 贾英民， 二阶动态智能体网络的一致性控制， http://www.paper.edu.cn/debug/downloadpaper.php?serial_number=200611-847&ty pe=l
[51]D.V. Dimarogonas and K.J. Kyriakopoulos, Connectivity preserving distributed swarm aggregation for multiple kinematic agents,46th IEEE Conf. Decision and Control, 2007:2913-2918.
[52] D.V. Dimarogonas and K.J. Kyriakopoulos, Connectivity Preserving State Agreement for Multiple Unicycles. American Control Conference, 2007,1179-1184
[53] M. M. Zavlanos and G. J. Pappas,Potential Fields for Maintaining Connectivity of Mobile Networks IEEE Transactions on Robotics, 2007(23)4:1-4
[54] M. M. Zavlanos and G. J. Pappas, Controlling connectivity of dynamic graphs, IEEE Conference on Decision and Control, 2005:6388-6393.
[55] M. M. Zavlanos, A. Jadbabaie, G. J. Pappas, Flocking while preserving network connectivity. Proc.of the IEEE Conference on Decision and Control, 2007:2919-2924.
[56] D.V. Dimarogonas and K.J Kyriakopoulos, Decentralized connectivity maintenance in mobile networks with bounded inputs, IEEE Conference on Robotics and Automation, Pasadena, CA, 2008:1507-1712
[57] M.C. De Gennaro and A. Jadbabaie, Decentralized control of connectivity for multi-agent systems. 45th IEEE Conference Decision and Control,2006: 3628-3633.
[58] M. Ji and M. Egerstedt.Connectedness preserving distibuted coordination control over dynamic graphs, American Control Conference, 2005: 93-98.
[59] M. Ji and M. Egerstedt.Distributed coordination control of multi-agent systems while preserving connectedness.IEEE Transactions on Robotics, 2007,23(4): 693 -703.
[60] W Wang, and J E Slotine, Contraction analysis of time-delayed communications and group cooperation. IEEE Trans on Automatic Control, 2006, 51 (4): 712-717.
[61] P. A. Bliman andG. Ferrari Trecate, Average consensus problems in networks of agents with delayed communications. Proceeding of the 44th IEEE Conference on Decision and Control, and the European Control Conference. Spain:Seville, 2005:7066-7071.
[62] 刘成林,田玉平,具有不同通信时延的多个体系统的一致性,东南大学学报,2008,38(1):170-174.
[63] Yuan Gong Sun, LongWang and Guangming Xie. Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays,Systems & Control Letters,2008,57:175-183
[64] Yuan Gong Sun, LongWang and Guangming Xie.Average Consensus in Directed Networks of Dynamic Agents with Time-Varying Communication Delays,45th IEEE Conference on Decision Control, San Diego, CA, USA, 2006:3393-3398
[65] P. Lin, Y. Jia, J. Du, and S. Yuan, Distributed consensus control for networks of second-order agents with fixed topology and time-delay. Proceedings of the 26th Chinese Control Conference, 2007:577-581.
[66] P. Lin and Y. Jia, Distributed robust H_∞ consensus control in directed networks of agents with time-delay, Systems and Control Letters, 2008,(57)8:643-653
[67] P. Lin and Y. Jia, Average-consensus in networks of multi-agents with both switching topology and coupling time-delay, Physica A, 2008,(387)1:303-313.
[68] Cheng Lin Liu and Yu Ping Tian, Coordination of Multi-agent Systems with Time-Varying Delays, Proceedings of the 27th Chinese Control Conference,Kunming 2008:76-80
[69] Cheng Lin Liu and Yu Ping Tian, Coordination of multi-agent system with communication delays. The International Federation of Automatic Control Seoul, Korea, July 6-11,2008:10782-10787
[70] J. Hu, Y. Hong, Leader-following coordination of multi-agent systems with coupling time delays. Physica A .2007: 853-863.
[71] H. G. Tanner, A. Jadbabaie, and G. J. Pappas, Stable flocking of mobile agents, part i: Fixed topology, in Proc. of CDC, (Maui, Hawaii), 2003: 2010-2015.
[72] H. G. Tanner, A. Jadbabaie, and G. J. Pappas, Stable flocking of mobile agents, part ii: Dynamic topology,in Proc. of CDC, (Maui, Hawaii), 2003: 2016-2021.
[73] R. O. Saber, A unified analytical look at Reynolds flocking rules, Technical Report 2003-014, California Institute of Technology, Control and Dynamical Systems,Pasadena, California, 2003
[74] N. E. Leonard and E. Fiorelli, Virtual leaders, artificial potentials and coordinated control of groups, in Proc. IEEE Conference on Decision and Control, Orlando,Florida USA, 2001, 3:2968-2973.
[75] R. O. Saber, Flocking for multi-agent dynamic systems: Algorithms and theory,IEEE Transactions on Automatic Control,2006,51(3):401-420.
[76] Long Wang, Hong Shi and Tianguang Chu, Flocking control of groups of mobile autonomous agents via local feedback, Proc of the 2005 IEEE International Symposium on Intelligent Control, Limassol, Cyprus, 2005:441-446.
[77] Hui Yu and Yongji Wang, Control of stable flocking motion of multi-agent with a leader, Journal of Huazhong University of Science and Technology (Nature Science Edition), 2005, 33(8): 56-58.
[78] Hui Yu and Yongji Wang,Stable flocking motion of mobile agents following a leader infixed and switching networks,International Journal of Automation and Computing, 2006,3(1):8-16
[79] Y. Liu, K. M. Passino, and M. Polycarpou, Stability analysis of m-dimensional asynchronous swarms with a fixed communication topology, IEEE Transactions on Automatic Control, 2003,48(1): 76-95.
[80] Housheng Su,Xiaofan Wang and Zongli Lin, Flocking of Multi-Agents with a Virtual Leader Part?: with a Minority of Informed Agents, 46th IEEE Conference on Decision and Control, New Orleans, LA, USA,2007: 12-14.
[81] Housheng Su,Xiaofan Wang and Zongli Lin, Flocking of Multi-Agents with a Virtual Leader Part ?: with a Virtual Leader of Varying Velocity,46th IEEE Conference on Decision and Control, New Orleans, LA, USA,2007: 12-14.
[82] R. O. Saber and R.M.Murray Flocking with Obstacle Avoidance: Cooperations with Limited Communication in Mobile Networks, IEEE Conference on Decision and Control, 2003,(2): 2022-2028
[83] R. O. Saber,Flocking with Obstacle Avoidance,Technical Report 2003-006,California Institute of Technology, Control and Dynamical Systems, Pasadena,California, February 2003,http://resolver.caltech.edu/CaltechCDSTR:2003.006.
[84] H. G. Tanner, Flocking with Obstacle Avoidance in Switching Networks of Interconnected Vehicles. IEEE International Conference Robotics and Automation,New Orleans LA, 2004:3006-3011.
[85] E. Rimon and D. Koditschek, Exact Robot Navigation Using Artificial Potential Functions.IEEE Transactions on Robotics and Automation. 1992, 8(5): 501-518.
[86] M Lindhe, P (?)gren and .K. H. Johansson ,Flocking with obstacle avoidance: A new distributed coordination algorithm based on Voronoi partitions, Robotics and Automation, Barcelona, Spain 2005: 1785-1790
[87]Yan fei Liu and K. M. Passino, Stable social foraging swarms in a noisy environment, IEEE Transaction on Automatic Control, 2004, 49(1): 30-44
[88]V. Gazi and K. M. Passino, Stability analysis of social foraging swarms, IEEE Transactions on Systems, Man, and Cybernetics -part B: Cybernetics, 2004,34(1): 539-556
[89]X. Li, J. Xiao, and Z. Cai, Stable flocking of swarms using local information, in Conference Proceedings IEEE International Conference on Systems, Man and Cybernetics, 2005, 3921-3926
[90]J. H. Reif and H. Wang, social potential fields: a distributed behavioral control for autonomous robots, Robotics and Autonomous Systems, 1999,27:171-194
[91]T. Balch and R. C. Arkin, Behavior-based formation control for multi-robot teams, IEEE Transaction on Robotics and Automation, 1998, 14(6): 926-939
[92]M.Schneider-Fontan, M.J Mataric, Territorial multi-robot task division, IEEE Trans. Robot, Autom, 1998, 14, 815-822
[93]J.R. Lawton, B. J. Young and R. W. Beard, A decentralized approach to elementary formation maneuvers, In: Proceeding of IEEE International Conference on Robotics and Automation, San Francisco, CA, 2000, 3:2728-2733
[94]J.R. Lawton, R.W.Beard, Synchronized multiple spacecraft rotations, Automatica, 2000, 38, (8), pp. 1359-1364
[95]Damian Dobroczynski, Multi-agent behavioral control system for a group of mobile robots, Second Workshop on Robot Motion and Control, 2001, 18-20
[96]苏治宝，陆际联，基于行为法队形保持中的队形反馈，机床与液压，2003，3： 167-169
[97]P.K.C. Wang. Navigation strategies for multiple autonomous mobile robots moving in formation, Journal of.Robot and System, 1991, 8(2): 177-195
[98]T. Sugar, V. Kumar, Decentralized control of cooperating mobile manipulators, Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium, May 1998, 2916-2921
[99]J.P. Desai, J. Ostrowski and V. Kumar.Controlling formations of multiple mobile robots, In: Proceeding of IEEE International Conference of Robot and Automation, Leuven, Belgium. 1998, 2864-2869
[100]H. Yamaguchi, J. W. Burdick. Asymptotic stabilization of multiple nonholonomic mobile robots forming group formations,Proceedings of IEEE International Conference on Robotics and Automation, Leuven, Belgium, 1998,3573-3580
[101]M.Mesbahi, F.Y. Hadaegh, Formation flying control of multiple spacecraft via graphs, matrix inequalities, and switching, J. Guid.Control Dyn., 2000, 24, 369-377
[102]R. W. Beard, J. Lawton and F. Y. Hadaegh, A coordination architecture for spacecraft formation control, IEEE Transaction on Control Systems Technology, 2000, 9(6): 777-790
[103]W.Ren, R. W. Beard, A decentralized scheme for spacecraft formation flying via virtual structure approach, Proceedings of the American Control Conference, Denver, Colorado, American Automatic Control Council, 2003: 1746-1751
[104]B. J. Young, R. W. Beard and J. M. Kelsey, A control scheme for improving multi-vehicle formation maneuvers, In: Proceeding of the American Control Conference, Arlington, VA, 2001, 2:704-709
[105]景兴建，王越超，谈大龙，基于人工协调场的多移动机器人实时协调避碰规划，控制理论与应用，2004，21(5)：757-764
[106]D. E. Koditschek, An approach to autonomous robot assembly, Robotica, 1994,12: 137-155
[107]H. Yamaguchi, Adaptive formation control for distributed autonomous mobile robot groups, In: Proceeding of the IEEE. International Conference on Robotics and Automation, Albuquerque, New Mexico, 1997, 3:2300-2305
[108]E. Rimon and D. E. Koditschek, exact robot navigation using artificial potential functions, IEEE Transaction on Robotics and Automation, 1992, 8(5): 501-518
[109]J. Finke, K. M ,Passino and S Ganapathy, Cooperative control via task load balancing for networked uninhabited autonomous vehicles, 42nd IEEE Conference on Decision and Control,Hawaii, 2003:31-36
[110]A,GilL,S Ganapathy and K. M ,Passino, Cooperative scheduling of tasks for networked autonomous vehicles, 42nd IEEE Conference on Decision and Control, Hawaii, 2003:522-527
[111]Y Liu and K. M Passino, Biomimicry of social foraging bacteria for distributed optimization: models, principles and emergent behaviors, Journal of Optimization Theory and Applications, 2002,115(3):603-628.
[112]K. M Passino, Biomimicry of bacterial foraging for distributed optimization and control, IEEE Control Systems Magazine,2002,22(3):52-67.
[113]V. Gazi, Swarm aggregations using artificial potentials and sliding mode control, IEEE Transactions on Robotics,2005,21 (6): 1208-1214.
[114]A. F. Filippov, Differential equations with discontinuous right-hand side. Mathematics and Its Applications (Soviet Series), Kluwer Academic Publishers, The Netherlands, 1988.
[ll5]H.Frank,Clarke,Optimization and Nonsmooth Analysis Classics in applied mathematics, 5.SIAM, Philadelphia, 1990.
[116]I. D Couzin, J .Krause and R.Jamesetl, Collective memory and spatial sorting in animal groups.Journal of Theoretical Biology, 2002, 218:1-11.
[117]高云园，韦巍．未知环境中基于免疫网络的多机器人自主协作．浙江大学学报(工学版)，2006,40(5)：733-737
[118]R.Winder, J. Reggia, Distributed partial Memories to Improve Self-Organizing collective movements.IEEE Trans. SMC B. 2004, 34:1967-1707.
[119]Alejandro Rodriguez and James A. Reggia, Extending self-organizing particle systems to problem solving.Artificial Life. 2004, 10 (4):379-395
[121]张纯刚，席裕庚．全局环境未知时基于滚动窗口的机器人路径规划．中国科学(E)辑，2001．31(2)51-58．
[122]李少逸，董慧颖，陈文波，基于Limit-cycle的机器人动态路径规划方法．沈阳工学院学报，2004，(23)1：50-53
[123]D. H. Kim, J. H. Kim, A real-time limit-cycle navigation method for fast mobile robot and its application to robot soccer.Robotics and Autonomous Systems, 2003,42( 1 ): 17-30.
[124]程拥强，蒋平，朱劲，郭凤龙，用势场法改进的极限环导航方法在移动机器人中的应用，机器人，2004,26(2)：133-138
[125] R. W. Beard, J. Lawton and F. Y. Hadaegh, A feedback architecture for formation control, in Proc. American Control Conference, June 28-30, 2000(6): 4087-4091.
[126] W.Ren, and R.W Beard, Virtual structure based spacecraft formation control with formation feedback. Presented at AIAA Guidance, Navigation, and Control Conf.,Monterey, CA, August 2002
[127] F. Zhang, W. Chen and Y. Xi, Motion synchronization of mobile robot networks:robustness, in Proc. of IEEE/RSJ Conf. on Intelligent Robots and Systems (IROS),Beijing, China, Oct. 2006:5570-5575.
[128] X. F. Wang and G. Chen, Synchronization in scale-free dynamical networks:Robustness and fragility, IEEE Trans. on Circ. and Syst.-I, 2002,(49)1: 54-62.
[129] B. Boyd, L.E. Ghaoui, E. Feron, V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, SIAM, Philadelphia, PA, 1994.
[130] Xi Li ,De Souza and Carlos E. Criteria for robust stability and stabilization of uncertain linear systems with state delay Automatica ,1997 ,33 (9) :1657-1662.
[131]Zili Li and Zengqiang Chen,A Criterion of the Consensus Problems in Multi-agent Systems with One Leader and Multi-follower. Proceedings of the 27th Chinese Control Conference, Kunming, China,2008,536-539.
[132] Feng Guo, Xizhao Wang and Yan Li, A new algorithm for solving convex hull problem and its application to feature selection, International conference on Machine learning and cybernetics, Kunming, 2008,369-373.