Existing coupled distributed estimation and motion control strategies of mobile sensor networks present limitations in velocity-varying target tracking. Therefore, a velocity-varying target tracking algorithm based on flocking control is proposed herein. The Kalman-consensus filter is utilized to estimate the position, velocity and acceleration of a target. The flocking control algorithm with a velocity-varying virtual leader enables the position of the center of the mobile sensor network to converge to that of the target. By applying an effective cascading Lyapunov method, stability analysis is performed. Simulation results are provided to validate the feasibility of the proposed algorithm.
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RAWAT P, SINGH K D, CHAOUCHI H, et al. Wireless sensor networks: A survey on recent developments and potential synergies [J]. The Journal of Supercomputing, 2014, 68(1): 1–48.
ZHANG Y, LU R Y, CAI Y Z. Missile-target situation assessment model based on reinforcement learning [J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(5): 561–568.
HALL D L, LLINAS J. An introduction to multisensor data fusion [J]. Proceedings of the IEEE, 1997, 85(1): 6–23.
SPANOS D P, OLFATI-SABER R, MURRAY R M. Dynamic consensus on mobile networks [C]// IFAC World Congress. Prague: IFAC, 2005: 1–6.
OLFATI-SABER R. Distributed Kalman filtering for sensor networks [C]// 2007 46th IEEE Conference on Decision and Control. New Orleans, LA: IEEE, 2007: 5492–5498.
WANG L, ZHANG G Z, ZHU H Y, et al. Adaptive consensus fusion estimation for mobile sensor networks [J]. Journal of Shanghai Jiao Tong University, 2011, 45(3): 383–387 (in Chinese).
ZHANG Y, TIAN Y P. A fully distributed weight design approach to consensus Kalman filtering for sensor networks [J]. Automatica, 2019, 104: 34–40.
LIU Q Y, WANG Z D, HE X, et al. On Kalman-consensus filtering with random link failures over sensor networks [J]. IEEE Transactions on Automatic Control, 2018, 63(8): 2701–2708.
OLFATI-SABER R, JALALKAMALI P. Coupled distributed estimation and control for mobile sensor networks [J]. IEEE Transactions on Automatic Control, 2012, 57(10): 2609–2614.
LOU K, CUI B T, LI W. Target tracking algorithm of mobile sensor networks based on flocking control [J]. Control and Decision, 2013, 28(11): 1637–1642 (in Chinese).
SU H S, CHEN X, CHEN M Z Q, et al. Distributed estimation and control for mobile sensor networks with coupling delays [J]. ISA Transactions, 2016, 64: 141–150.
JENABZADEH A, SAFARINEJADIAN B. Distributed tracking control problem of Lipschitz multiagent systems with external disturbances and input delay [J]. Systems Science & Control Engineering, 2018, 6(1): 268–278.
LUO X Y, LI X L, LI S B, et al. Flocking for multiagent systems with optimally rigid topology based on information weighted Kalman consensus filter [J]. International Journal of Control, Automation and Systems, 2017, 15(1): 138–148.
SU H S, WANG X F, LIN Z L. Flocking of multiagents with a virtual leader [J]. IEEE Transactions on Automatic Control, 2009, 54(2): 293–307.
YU W W, CHEN G R, CAO M. Distributed leader-follower flocking control for multi-agent dynamical systems with time-varying velocities [J]. Systems & Control Letters, 2010, 59(9): 543–552.
ZHAO X W, GUAN Z H, LI J, et al. Flocking of multi-agent nonholonomic systems with unknown leader dynamics and relative measurements [J]. International Journal of Robust and Nonlinear Control, 2017, 27(17): 3685–3702.
GAO J Y, XU X, DING N, et al. Flocking motion of multi-agent system by dynamic pinning control [J]. IET Control Theory & Applications, 2017, 11(5): 714–722.
Foundation item: the National Natural Science Foundation of China (No. 61627810), the Joint Fund of Advanced Aerospace Manufacturing Technology Research (No. 2017-JCJQ-ZQ-031), and the National Science and Technology Major Program of China (No. 2018YFB1305003)
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Zhang, L., Dong, X., Yao, L. et al. Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking Control. J. Shanghai Jiaotong Univ. (Sci.) 26, 446–453 (2021). https://doi.org/10.1007/s12204-021-2283-7
- mobile sensor network
- velocity-varying target tracking
- flocking control
- Kalman-consensus filtering
- TP 273