Variable Structure Behavioural Controller for Multi-agent Systems

Document Type : Research Paper

Authors

School of Mechanical Engineering, Sharif University of Technology, Tehran

Abstract

In previous papers authors have considered agents as inertia-less self driven particles and designed a flocking algorithm. Application of this algorithm to agents with considerable inertial characteristics needs a behavioural controller. The controller uses the local information and helps every agent to imitate the desired behaviour as a member of the flocking frame which covers the main issue in this paper. All agents are assumed to possess limited identical influencing/sensing radius. The sliding-mode control technique is used, hence; effect of bounded disturbances and uncertainties can be omitted too. Once inertial agents are equipped with the behavioural controller, the multi-agent system behaves similar to a group of self-driven inertia-less particles which; coordination control algorithms and cohesion analyses are previously designed for.

Keywords

References

[1]   Brogan, D.C., and Hodgins, J.K., “Group Behaviors for Systems with Significant Dynamics,” Autonomous Robots, Vol. 4, pp. 137-153, (1997).
[2]   Khatib, O., “Real Time Obstacle Avoidance for Manipulators and Mobile Robots”, International Journal of Robotics Research, Vol. 5, No. 1, pp. 90- 99, (1986).
[3]   Reif, J.H., and Wang, H., “Social Potential Fields: A Distributed Behavioral Control for Autonomous Robots”, Robotics and Autonomous Systems, Vol. 27, pp. 171-194, (1999).
[4]   Gazi, V., and Passino, K.M., “Stability Analysis of Social Foraging Swarms”, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, Vol. 34, No. 1, pp. 539-557, (2004).
[5]   Etemadi, S., Alasty, A., and Vossoughi, G.R., “Stability Analysis of Robotic Swarm with Limited Field of View”, Proceeding of the ASME International Mechanical Engineering Congress and Exposition, Washington, USA, pp. 175-184, (2007).
[6]   Etemadi, S., Alasti, A., and Vossoughi G.R., “Stability Investigation of a Robotic Swarm with Limited Field of View”, Proceedings of IFAC World Congress, Seoul, Korea, Vol. 17, No. 1, pp. 10794-10799, (2008).
[7]   Dimarogonas, D.V., Kyriakopoulos, K.J., “A Connection Between Formation Infeasibility and Velocity Alignment in Kinematic Multi-agent Systems”, Automatica, Vol. 44, No. 10, pp. 2648-2654, (2008).
[8]   Kim, D.H., Wang, H., and Shin, S., “Decentralized Control of Autonomous Swarm Systems Using Artificial Potential Functions: Analytical Design Guidelines”, Journal of Intelligent and Robotic Systems, Vol. 45, pp. 369–394, (2006).
[9]   Burger, M., Capasso, V., and Morale, D., “On an Aggregation Model with Long and Short Range Interactions”, Nonlinear Analysis: Real World Applications, Vol. 8, pp. 939–958, (2007).
[10]     Bıyık, E., and Arcak, M., “Area Aggregation and Time-scale Modeling for Sparse Nonlinear Networks”, Systems and Control Letters, Vol. 57, pp. 142–149, (2008).
[11]     Haddad, W.M., and Hui1, Q., “Complexity, Robustness, Self-organization, Swarms, and System Thermodynamics”, Nonlinear Analysis: Real World Applications, Vol. 10, pp. 531–543, (2009).
[12]     Vicsek, T., Czirok, A., Jacob, E. B., Cohen, I., and Schochet, O., “Novel Type of Phase Transitions in a System of Self-driven Particles”, Physical Review Letters, Vol. 75, pp. 1226-1229, (1995).
[13]    Jadbabaie, A., Lin, J., and Morse, A.S., “Coordination of Groups of Mobile Autonomous Agents using Nearest Neighbor Rules”, IEEE Transactions on Automatic Control, Vol. 48, No. 6, pp. 988-1001, (2003).
[14]    Olfati Saber, R., “Flocking for Multi Agent Dynamic Systems: Algorithms and Theory”, IEEE Transactions on Automatic Control, Vol. 51, No. 3, pp. 401-420, (2006).
[15]     Starke, J., Kaga, T., Schanz, M., and Fukuda, T., “Experimental Study on Self Organized and Error Resistant Control of Distributed Autonomous Robotic Systems”, International Journal of Robotic Research, Vol. 24, No. 6, pp. 465-486, (2005).
[16]     Kim, D.H., and Shin, S., “Self-organization of Decentralized Swarm Agents Based on Modified Particle Swarm Algorithm”, Journal of Intelligent and Robotic Systems, Vol. 46, pp. 129–149, (2006).
[17]     Krishnanand, K.N., and Ghose, D., “Theoretical Foundations for Rendezvous of Glowworm-inspired Agent Swarms at Multiple Locations”, Robotics and Autonomous Systems, Vol. 56, pp. 549–569, (2008).
[18]    Porfiri, M., Roberson, D.G., and Stilwell, D.J., “Tracking and Formation Control of Multiple Autonomous Agents: A Two-level Consensus Approach”, Automatica, Vol. 43, pp. 1318–1328, (2007).
[19]     Su, H., Wang, X., and Yang, W., “Flocking in Multi-agent Systems with Multiple Virtual Leaders”, Asian Journal of Control, Vol. 10, No. 2, pp. 238-245, (2008).
[20]     Liu, Y., Passino, K.M., and Polycarpou, M., “Stability Analysis of M Dimensional Asynchronous Swarms with a Fixed Communication Topology”, IEEE Transactions on Automatic Control, Vol. 48, No. 1, pp. 76-95, (2003).
[21]     Hong, Y., Chen, G., and Bushnell, L., “Distributed Observers Design for Leader-following Control of Multi-agent Networks”, Automatica, Vol. 44, pp. 846–850, (2008).
[22]     Etemadi, S., Alasty, A., and Vossoughi, G.R., “Nonlinear Tracking Control of Robotic Swarm,” Proceedings of ISME International Mechanical Engineering Conference (CD), Kerman Iran, Paper No. 1678, (2008).
[23]     Vatankhah, R., Etemadi, S., Honarvar, M., Alasty, A., Boroushaki, M., and Vossoughi, G.R., “Online Velocity Optimization of Robotic Swarm Flocking using Particle Swarm Optimization (PSO) Method,” Proceedings of ISMA09 Conference (CD), Sharjah, UAE, Paper No. 56-14717, DOI. 10.1109/ISMA.2009.5164776, (2009).
 
[24]      Su, H., Wang, X., and Chen, G., “A Connectivity-preserving Flocking Algorithm for Multi-agent Systems Based only on Position Measurements,”. International Journal of Control, Vol. 82, No. 7, pp. 1334-1343, (2009).
[25]     Gazi, V., “Swarm Aggregations using Artificial Potentials and Sliding Mode Control,” IEEE Transactions on Robotics, Vol. 21, No. 6, pp. 1208-1214, (2005).
[26]     Gazi, V., Fidan, B., Hanay, Y. S., and Koksal, M. I., “Aggregation, Foraging, and Formation Control of Swarms with Non-holonomic Agents using Potential Functions and Sliding Mode Techniques,” Turkish Journal of Electrical Engineering, Vol. 15, No. 2, pp. 149-168, (2007).
[27]     Alasty, A., Etemadi, S., and Roshan-Ghalb, F., "Behavioral Control of Autonomous Swarms," Proceedings of ISME International Mechanical Engineering Conference (CD), Kerman Iran, Paper No. 2758, (2008).
[28]     Etemadi, S., Vatankhah, R., Alasty, A., and Vossoughi, G.R., ”Swarm Aggregation Using Emotional Learning Based Intelligent Controller,” Proceedings of ISMA09 Conference (CD), Sharjah, UAE, Paper No. 56-69446, DOI. 10.1109/ ISMA, 5164827, (2009).
Iranian Journal of Mechanical Engineering Transactions of the ISME
Volume 10, Issue 2 - Serial Number 13
September 2009
Pages 49-63

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