多智能体系统的估计、干预及非线性耦合算法

胡江平; 刘志新; 王金环; 王琳; 胡晓明

doi:10.3724/SP.J.1004.2013.01796

多智能体系统的估计、干预及非线性耦合算法

doi: 10.3724/SP.J.1004.2013.01796

1.
电子科技大学自动化工程学院成都 611731;
2.
中国科学院数学与系统科学研究院北京 100080;
3.
河北工业大学理学院天津 300401;
4.
上海交通大学自动化系上海 200240;
5.
瑞典皇家工学院数学系斯德哥尔摩 10044

基金项目:

Supported by National Natural Science Foundation of China (61104104, 60804043, 61273221, 61104137, 61203142)

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- 文章访问数: 1929
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- 被引次数: 0
出版历程
- 收稿日期: 2013-07-01
- 修回日期: 2013-08-29
- 刊出日期: 2013-11-20

Estimation, Intervention and Interaction of Multi-agent Systems

1.
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;
2.
Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;
3.
School of Sciences, Hebei University of Technology, Tian-jin 300401, China;
4.
Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China 5. Department of Math-ematics, Royal Institute of Technology (KTH), Stockholm 10044, Sweden

Funds:

Supported by National Natural Science Foundation of China (61104104, 60804043, 61273221, 61104137, 61203142)

More Information

Corresponding author: HU Jiang-Ping

摘要

摘要: 对多智能体系统的最新研究进展进行了简要评述. 我们主要关注以下三个方面的研究成果: 分布式估计和滤波算法, 基于外部途径的干预算法以及非线性耦合控制算法等.
- 多智能系统 /
- 协调控制 /
- 分布式估计 /
- 软控制 /
- 非线性耦合
Abstract: In this paper we provide a brief survey on recent research on multi-agent systems. We focus on results in three areas of the research, namely, estimation andfltering, intervention by external means, and interactive control.
- Distributed estimation /
- cooperativeflter /
- soft control /
- state-topology coevolution /
- nonlinear consensus control

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参考文献(82)

[1]	Fax J A, Murray R M. Information flow and cooperative control of vehicle formations. IEEE Transactions on Automatic Control, 2004, 49(9): 1465-1476
[2]	Olfati-Saber R, Fax J A, Murray R M. Consensus and cooperation in networked multi-agent systems. Proceedings of IEEE, 2007, 95(1): 215-233
[3]	Jadbabaie A, Lin J, Morse A S. Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Transactions on Automatic Control, 2003, 48(6): 988-1001
[4]	Buhl J, Sumpter D J T, Couzin D, Hale J J, Despland E, Miller E R, Simpson S J. From disorder to order in marching locusts. Science, 2006, 312(5778): 1402-1406
[5]	Couzin I D, Krause J, Franks N R, Levin S A. Effective leadership and decision-making in animal groups on the move. Nature, 2005, 433(7025): 513-516
[6]	Olfati-Saber R. Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Transactions on Automatic Control, 2006, 51(3): 401-420
[7]	Han J, Li M, Guo L. Soft control on collective behavior of a group of autonomous agents by a shill agent. Journal of Systems Science and Complexity, 2006, 19(1): 54-62
[8]	Yang P, Freeman R, Lynch K. Multi-agent coordination by decentralized estimation and control. IEEE Transactions on Automatic Control, 2008, 53(11): 2480-2496
[9]	Olfati-Saber R, Jalalkamali P. Coupled distributed estimation and control for mobile sensor networks. IEEE Transactions on Automatic Control, 2012, 57(10): 2609-2614
[10]	Hu J P, Hu X M. Optimal target trajectory estimation and filtering using networked sensors. Journal of Systems Science and Complexity, 2008, 21(3): 325-336
[11]	Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic. Nature, 2000, 407(6803): 487-490
[12]	Moussard M, Helbing D, Theraulaz G. How simple rules determine pedestrian behavior and crowd disasters. Proceedings of the National Academy of the Sciences of the United States of America, 2011, 108(17): 6884-6888
[13]	Hong Y G, Hu J P, Gao L X. Tracking control for multi-agent consensus with an active leader and variable topology. Automatica, 2006, 42(7): 1177-1182
[14]	Hong Y G, Chen G R, Bushnell L. Distributed observers design for leader-following control of multi-agent networks. Automatica, 2008, 44(3): 846-850
[15]	Ren W. On consensus algorithms for double-integrator dynamics. IEEE Transactions on Automatic Control, 2008, 53(6): 1503-1509
[16]	Li J Z, Ren W, Xu S Y. Distributed containment control with multiple dynamic leaders for double-integrator dynamics using only position measurements. IEEE Transactions on Automatic Control, 2012, 57(6): 1553-1559
[17]	Hu J P, Feng G. Distributed tracking control of leader-follower multi-agent systems under noisy measurement. Automatica, 2010, 46(8): 1382-1387
[18]	Gustavi T, Hu X. Observer-based leader-following formation control using onboard sensor information. IEEE Transactions on Robotics, 2008, 24(6): 1457-1462
[19]	Xiang J, Wei W, Li Y J. Synchronized output regulation of linear networked systems. IEEE Transactions on Automatic Control, 2009, 54(6): 1336-1341
[20]	Huang J. Remarks on “synchronized output regulation of linear networked systems”. IEEE Transactions on Automatic Control, 2011, 56(3): 630-631
[21]	Kim H, Shim H, Seo J H. Output consensus of heterogeneous uncertain linear multi-agent systems. IEEE Transactions on Automatic Control, 2011, 56(1): 200-206
[22]	Wieland P, Sepulchre R, Allgower F. An internal model principle is necessary and sufficient for linear output synchronization. Automatica, 2011, 47(5): 1068-1074
[23]	Wang X L, Hong Y G, Huang J, Jiang Z P. A distributed control approach to a robust output regulation problem for multi-agent linear systems. IEEE Transactions on Automatic Control, 2010, 45: 2891-2895
[24]	Su Y, Hong Y, Huang J. A general result on the robust cooperative output regulation for linear uncertain multi-agent systems. IEEE Transactions on Automatic Control, 2013, 58(5): 1275-1279
[25]	Bar-Shalom Y, Li X R. Multitarget-Multisensor Tracking: Principles and Techniques. Storrs, CT: YBS Publishing, 1995
[26]	Olfati-Saber R, Shamma J S. Consensus filters for sensor networks and distributed sensor fusion. Proceedings of the 44th IEEE Conference on Decision and Control and 2005 European Control Conference. Seville, Spain, 2005, 6698-6703
[27]	Jazwinski A H. Stochastic Processes and Filtering Theory. Mineola NY: Dover Publications, 2007
[28]	Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear system. In: Proceedings of the 1995 American Control Conference. Washington, DC: IEEE, 1995: 1628-1632
[29]	Doucet A, Freitas N D, Gordon N J. Sequential Monte Carlo Methods in Practice. New York: Springer, 2001
[30]	Reif K, Gunther S, Yaz E, Unbehauen R. Stochastic stability of the continuous-time extended Kalman filter. IEE Proceedings Control Theory and Applications, 2000, 147(1): 45-52
[31]	Hu J P, Hu X M. Nonlinear filtering in target tracking using cooperative mobile sensors. Automatica, 2010, 46(12): 2041-2046
[32]	Wang X F, Chen G R. Pinning control of scale-free dynamical networks. Physica A, 20002, 310(3-4): 521-531
[33]	Vicsek T, Czirók A, Ben-Jacob E, Cohen I, Sochet O. Novel type of phase transition in a system of self-driven particles. Physical Review Letters, 1995, 75(6): 1226-1229
[34]	Cucker F, Smale S. Emergent behavior in flocks. IEEE Transactions on Automatic Control, 2007, 52(5): 852-862
[35]	Liu Z X, Guo L. Connectivity and synchronization of vicsek model. Science in China: Series F, 2008, 51(7): 848-858
[36]	Liu Z X, Guo L. Synchronization of multi-agent systems without connectivity assumptions. Automatica, 2009, 45(12): 2744-2753
[37]	Chen G, Liu Z X, Guo L. The smallest possible interaction radius for flock synchronization. SIAM Journal of Control and Optimization, 2012, 50(4): 1950-1970
[38]	Han J, Wang L. Nondestructive intervention to multi-agent systems through an intelligent agent. PLoS ONE, 2013, 8(5): e61542. DOI: 10.1371/journal.pone.0061542
[39]	Wang L, Guo L. Robust consensus and soft control of multi-agent systems with noises. Journal of Systems Science and Complexity, 2008, 21(3): 406-415
[40]	Wang X, Han J, Han H. Special agents can promote cooperation in the population. PLoS ONE, 2011, 6(12): e29182. DOI: 10.1371/journal.pone.0029182
[41]	Makris N, Ratilal P, Jagannathan S, Gong Z, Andrews M, Bertsatos I. Critical population density triggers rapid formation of vast oceanic fish shoals. Science, 2009, 323(5922): 1734-1737
[42]	Leonard N E, Shen T, Nabet B, Scardovi L, Couzinc I D, Levin S A. Decision versus compromise for animal groups in motion. Proceedings of the National Academy of the Sciences of the United States of America, 2012, 109(1): 227-232
[43]	Wang P K C, Hadaegh F Y. Coordination and control of multiple microspacecraft moving in formation. The Journal of the Astronautical Sciences, 1996, 44(3): 315-355
[44]	Kapila V, Sparks A G, Buffington J M, Yan Q G. Spacecraft formation flying: dynamics and control. Journal of Guidance, Control, Dynamics, 2000, 23(3): 561-564
[45]	Liu Z X, Han J, Hu X M. The proportion of leaders needed for the expected consensus. Automatica, 2011, 47(12): 2697-2703
[46]	Olfati-Saber R, Murray R M. Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions Automatic Control, 2004, 49(9): 1520-1533
[47]	Cheng D Z, Wang J H, Hu X M. An extension of LaSalle's invariance principle and its application to multi-agent consensus. IEEE Transactions Automatic Control, 2008, 52(7): 1765-1770
[48]	Li Z, Duan Z, Chen G, Huang L. Consensus of multi-agent systems and synchronization of complex networks: a unified viewpoint. IEEE Transactions Circuits and Systems-I Regular Papers, 2010, 57(1): 213-224
[49]	Tang Y T, Hong Y G. Hierarchical distributed control design for multi-agent systems using approximate simulation. Acta Automatica Sinica, 2013, 39(6): 868-874
[50]	Moreau L. Stability of multiagent systems with time-dependent communication links. IEEE Transactions Automatic Control, 2005, 50(2): 169-182
[51]	Jadbabaie A, Motee N, Barahona M. On the stability of the Kuramoto model of coupled nonlinear oscillators. Proceedings of the 2004 American Control Conference. Boston, MA, 2004, 0743-1619
[52]	Lin Z Y, Francis B, Maggiore M. State agreement for continuous-time coupled nonlinear systems. SIAM Journal on Control and Optimization, 2007, 46(1): 288-307
[53]	Angeli D, Bliman P A. Stability of leaderless discrete-time multi-agent systems. Mathematics of Control, Signals, and Systems, 2006, 18(4): 293-322
[54]	Chen Y, Lv J H, Lin Z L. Consensus of discrete-time multi-agent systems with transmission nonlinearity. Automatica, 2013, 49(6): 1768-1775
[55]	Lorenz J, Lorenz D A. On conditions for convergence to consensus. IEEE Transactions on Automatic Control, 2010, 55(7): 1651-1656
[56]	Hui Q, Haddad W M. Distributed nonlinear control algorithms for network consensus. Automatica, 2008, 44(9): 2375-2381
[57]	Li H, Liao X F, Lei X Y, Huang T W, Zhu W. Second-order consensus seeking in multi-agent systems with nonlinear dynamics over random switching directed networks. IEEE Transactions on Circuits and Systems---I: Regular Papers, 2013, 60(6): 1595-1607
[58]	Yang H, Jiang B, Cocquempot V, Zhan H G. Stabilization of switched nonlinear systems with all unstable modes: application to multi-agent systems. IEEE Transactions Automatic Control, 2011, 56(9): 2230-2235
[59]	McCabe C, Watson R, Prichard J S, Hall W. The web as an adaptive network: coevolution of web behavior and web structure. In Web Science Conference 2011, Koblenz German, 2011, 1-7.
[60]	Funk S, Salathe M, Jansen V A A. Modelling the influence of human behavior on the spread of infectious diseases: a review. Journal of the Royal Society Interface, 2010, 7(50): 1247-1256
[61]	Lee S M, Holme P, Wu Z X. Emergent hierarchical structures in multiadaptive games. Physical Review Letters, 2011, 106(2): 028702
[62]	Schmittmann B, Mukhopadhyay A. Opinion formation on adaptive networks with intensive average degree. Physical Review E, 2010, 82(6): 066104
[63]	Gross T, Blasius B. Adaptive coevolutionary networks: a review. Journal of the Royal Society: Interface, 2008, 5(20): 259-271
[64]	Alberts B. Special issue: complex systems and networks. Science, 2009, 325(5939): 405-432
[65]	Vicsek T, Zafiris A. Collective motion. Physics Reports, 2012, 517 (3-4), 71-140
[66]	Ren W, Cao Y C. Distributed Coordination of Multi-Agent Networks: Emergent Problems, Models, and Issues. New York: Springer, 2011
[67]	Yan W S, Li J B, Wang Y T. Consensus for damaged multi-agent system. Acta Automatica Sinica, 2012, 38(11): 1127-1133
[68]	Wang L, Wang X F. New conditions for synchronization in dynamical communication networks. Systems and Control Letters, 2011, 60(4): 219-225
[69]	Tang G G, Guo L. Convergence of a class of multi-agent systems in probabilistic framework. Journal of Systems Science and Complexity, 2007, 20(2): 173-197
[70]	Ballerini M, Cabibbo N, Candelier R, Cavagna A, Cisbani E, Giardina I. Interaction ruling animal collective behavior depends on topological rather than metric distance: evidence from a field study. Proceedings of the National Academy of the Sciences of the United States of America , 2008, 105(4): 1232-1237
[71]	Wang L, Wang X F, Hu X M. Synchronization of multi-agent systems with topological interaction. Proceedings of the 18th IFAC World Congress (IFAC), Milan: IFAC, 2011, 14642-14647
[72]	Chen C, Chen G, Guo L. Synchronization of mobile autonomous agents with M-nearest-neighbor rule. Proceedings of the 31st Chinese Control Conference. Hefei 2102. 1147-1152
[73]	Zavlanos M M, Pappas G J. Potential fields for maintaining connectivity of mobile networks. IEEE Transactions on Robotics, 2007, 23(4): 812-816
[74]	Ji M, Egerstedt M. Distributed coordination control of multiagent systems while preserving connectedness. IEEE Transactions on Robotics, 2007, 23(4): 693-703
[75]	Dimarogonas D V, Kyriakopoulos K J. Connectedness preserving distributed swarm aggregation for multiple kinematic robots. IEEE Transactions Robotics, 2008, 24(5): 1213-1223
[76]	Su H S, Wang X F, Chen G R. A connectivity-preserving flocking algorithm for multi-agent systems based only on position measurements. International Journal of Control, 2009, 82(7): 1334-1343
[77]	Zavlanos M M, Tanner H G, Jadbabaie A, Pappas G J. Hybrid control for connectivity preserving flocking. IEEE Transactions on Automatic Control, 2009, 54(12): 2869-2875
[78]	Su H S, Wang X F, Chen G R. Rendezvous of multiple mobile agents with preserved network connectivity. Systems and Control Letters, 2010, 59(5): 313-322
[79]	Ajorlou A, Momeni A, Aghdam A G. A class of bounded distributed control strategies for connectivity preservation in multi-agent systems. IEEE Transactions on Automatic Control, 2010, 55(12): 2828-2833
[80]	Dimarogonas D V, Johansson K H. Bounded control of network connectivity in multi-agent systems. IET Control Theory and Applications, 2010, 4(8): 1330-1338
[81]	Wang L, Wang X F, Hu X M. Connectivity preserving flocking without velocity measurement. Asian Journal of Control, 2013, 15(2): 521-532
[82]	Ajorlou A, Aghdam A G. Connectivity preservation in nonholonomic multi-agent systems: a bounded distributed control strategy. IEEE Transactions on Automatic Control, 2013, 58(9): 2366-2371