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Formation control of underwater vehicles using Multi Agent System

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Języki publikacji
EN
Abstrakty
EN
This paper proposes the development of a formation control algorithm of multiple acoustic underwater vehicles by employing the behaviour of autonomous mobile agents under a proposed pursuit. A robust pursuit is developed using the distributed consensus coordinated algorithm ensuring the transfer of information among the AUVs. The development of robust pursuit based on characteristics of multi-agent system is for solving the incomplete information capabilities in each agent such as asynchronous computation, decentralized data and no system global control. In unreliable and narrow banded underwater acoustic medium, the formation of AUVs based distributed coordinated consensus tracking can be accomplished under the constant or varying virtual leader’s velocity. Further, the study to achieve tracking based on virtual leader AUV’s velocity is extended to fixed and switching network topologies. Again for mild connectivity, an adjacency matrix is defined in such a way that an adaptive connectivity is ensured between the AUVs. The constant virtual leader vehicle velocity method based on consensus tracking is more robust to reduce inaccuracy because no accurate position and velocity measurements are required. Results were obtained using MATLAB and acquired outcomes are analysed for efficient formation control in presence of the underwater communication constraints.
Rocznik
Strony
365--384
Opis fizyczny
Bibliogr. 39 poz., rys., tab., wykr., wzory
Twórcy
  • Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla-768018, Odisha, India
  • School of Electrical Sciences, Indian Institute of Technology, Goa, India
  • Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla-768018, Odisha, India
Bibliografia
  • [1] J. W. Nicholson and A. J. Healey: The Present State of Autonomous Underwater Vehicle (AUV) Applications and Technologies, Marine Technology Society Journal, 42(1) (2008), 44-51.
  • [2] D. R. Blidberg: The Development of Autonomous Underwater Vehicles (AUV); A Brief Summary, IEEE ICRA, Lee New Hampshire, USA, 4. 2001.
  • [3] C. C. Sotzing and D. M. Lane: Improving the coordination efficiency of limited-communication multi-autonomus underwater vehicle operations using a multiagent architecture, Journal of Field Robotics, 27(4) (2010), 412-419.
  • [4] T. I. Fossen: Guidance and Control of Ocean Vehicles, John Wiley and sons Ltd., New York, 1994.
  • [5] X. Kang, H. Xu, and X. Feng: Fuzzy logic based behavior fusion for multi-AUV formation keeping in uncertain ocean environment, IEEE OCEANS 2009, Oct., 2009, pp. 1-7.
  • [6] F. Fahimi: Sliding mode formation control for under-actuated surface vessels, IEEE Trans. on Robotics, 23(3) (2007), 617-622.
  • [7] E. Yang and D. Gu: Nonlinear formation-keeping and mooring control of multiple autonomous underwater vehicles, IEEE/ASME Trans. Mechatronics, 12(2) (2007), 164-178.
  • [8] J. P. Desai, J. P. Ostrowski, and V. Kumar: Modeling and Control of Formations of Nonholonomic Mobile Robots, IEEE Trans. on Robotics And Automation, 17(6) (2001), 905-908.
  • [9] Y. Dai and S. G. Lee: The Leader-Follower Formation Control of Nonholonomic Mobile Robots, International Journal of Control, Automation, and Systems, 10(2) (2012), 350-361.
  • [10] B. Das, B. Subudhi, and B. B. Pati: Adaptive sliding mode formation control of multiple underwater robots, Archives of Control Sciences, 24(4) (2014), 515-543.
  • [11] L. Sorbi, G. Pio De Capua, L. Toni, and J. Fontaine: Target detection and recognition: A mission planner for Autonomous Underwater Vehicles, OCEANS 2011, Sept. 2011, pp. 19-22.
  • [12] H. Jung and D. H. Kim: Potential-Function-based Shape Formation in Swarm Simulation, International Journal of Control, Automation, and Systems, 12(2) (2014), 442-449.
  • [13] T. Balch and R. Arkin: Behavior-based formation control of multi-robot teams, IEEE Trans. on Robotics and Automation, 14(6) (1998), 926-939.
  • [14] G. Lafferriere, A. Williams, J. Caughman, and J. Veerman: Decentralized control of vehicle formations, System and Control Letters, 54(9) (2005), 899–910.
  • [15] R. Ghabcheloo, I. Kaminer, A. P. Aguiar, and A. Pascoal: A General Framework for MultipleVehicle Time-Coordinated Path Following Control, Amer. Control Conf., MO, USA, Jun. 2009, pp. 3071-3076.
  • [16] F. Dorfler and B. Francis: Geometric Analysis of the Formation Problem for Autonomous Robots, IEEE Trans. Automat. Contr., 55(10) (2010), 2379-2384.
  • [17] F. Zhang: Geometric Cooperative Control of Particle Formations, IEEE Trans. Automatic Contr., 55(3) (2010), 800-804.
  • [18] B. Das, B. Subudhi, and B. B. Pati: Co-operative control coordination of a team of underwater vehicles with communication constraints, Transactions of the Institute of Measurement and Control, 3(4) (2016), 463-481.
  • [19] D. Gu and H. Hu: Using fuzzy logic to design separation function in flocking algorithms, IEEE Trans. Fuzzy Syst., 2008, 16(4), pp. 826-838.
  • [20] R. O. Saber: Flocking for multi-agent dynamic systems: algorithms and theory, IEEE Trans. Automatic Control, 51(3) (2006), 401-420.
  • [21] B. Das, B. Subudhi, and B. B. Pati: Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment, Journal of Marine Engineering & Technology, 15(3) (2016), 135-151.
  • [22] D. Gu and Z. Wang: Leader-follower flocking: algorithms and experiments, IEEE Trans. on Control Systems Technology, 17(5) (2009), 1211-1219.
  • [23] I. S. Kulkarni and D. Pompili: Task allocation for networked autonomous underwater vehicles in critical missions, IEEE Journal on Selected Areas in Communications, 28(5) (2010), 716-727.
  • [24] H. Yang, C. Wang, and F. Zhang: A decoupled controller design approach for formation control of autonomous underwater vehicles with time delays, IET Control Theory Appl., 7(15) (2013), 1950-1958.
  • [25] P. Rattanasiri, P. A. Wilson, and A. B. Phillips: Numerical investigation of a fleet of towed AUVs, Ocean Engineering, 80(1) (2014), 25-35.
  • [26] J. Cortés, S. Martínez, and F. Bullo: Robust rendezvous for mobile autonomous agents via proximity graphs in arbitrary dimensions, IEEE Transactions on Autom. Control, 51(8) (2006), 1289-1298.
  • [27] J. A. Marshall, M. E. Broucke, and B. A. Francis: Formations of vehicles in cyclic pursuit, IEEE Transactions on Automatic Control, 49(11) (2004), 1963-1974.
  • [28] B. Das, B. Subudhi, and B. B. Pati: Cooperative formation control of Autonomous underwater vehicles: An Overview, International Journal of Automation and Computing, 13(3) (2016), 199-225.
  • [29] Y. G. Sun, L. Wang, and G. Xie: Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays, Systems & Control Letters, 57(2) (2008), 175-183.
  • [30] X. Xiang, G. Xu, Q. Zhang, Z. Xiao, and X. Huang: Coordinated control for multi-AUV systems based on hybrid automata, IEEE International Conference on Robotics and Biomimetics, 2007, 2121-2126.
  • [31] S. Liu, D. Wang, and E. Poh: Non-linear output feedback tracking control for AUVs in shallow wave disturbance condition, International Journal of Control, 81(11) (2008), 1806-1823.
  • [32] Y. Cao and W. Ren: Distributed Coordinated Tracking With Reduced Interaction via a Variable Structure Approach, IEEE Transactions on Automatic Control, 57(1) (2012), 33-48.
  • [33] F. Y. Bi, Y. J. Wei, J. Z. Zhang, and W. Cao: Position-tracking control of underactuated autonomous underwater vehicles in the presence of unknown ocean currents, IET Control Theory & Applications, 4(11) (2010), 2369-2380.
  • [34] S. Sariel, T. Balch, and N. Erdogan: Naval mine countermeasure missions, IEEE Robotics & Automation Magazine, 15(1) (2008), 45-52.
  • [35] Z. Hu, C. Ma, L. Zhang, A. Halme, T. Hayat, and B. Ahmad: Formation control of impulsive networked autonomous underwater vehicles under fixed and switching topologies, Neurocomputing, 147 (2015), 291-298.
  • [36] B. Das, B. Subudhi, and B. B. Pati: Employing Nonlinear observer for formation control of AUVs under communication constraints, Int. J. Intell. Unmanned Syst., 3(2/3) (May 2015), 122-155.
  • [37] L. Ding, Q. Han, and G. Guo: Network-based leader-following consensus for distributed multi-agent systems, Automatica, 49(7) (2013), 2281-2286.
  • [38] B. Frankovic and I. Budinska: Creation of intelligent distributed control system based on multi-agent technology, Journal of Electrical Engineering, 60(1) (2009), 29-33.
  • [39] C. J. F. Silvestre: Multi-Objective Optimization Theory with Applications to the Integrated Design of Controllers/Plants for Autonomous Vehicles, Ph. D Thesis, Technical Institute of Lisbon, Jun. 2000.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-faf6f156-e1ca-44f5-93da-6e8ecc712343
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