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Volume 8 Issue 12
Dec.  2021

IEEE/CAA Journal of Automatica Sinica

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Yiguo Yang, Liefa Liao, Hong Yang and Shuai Li, "An Optimal Control Strategy for Multi-UAVs Target Tracking and Cooperative Competition," IEEE/CAA J. Autom. Sinica, vol. 8, no. 12, pp. 1931-1947, Dec. 2021. doi: 10.1109/JAS.2020.1003012
Citation: Yiguo Yang, Liefa Liao, Hong Yang and Shuai Li, "An Optimal Control Strategy for Multi-UAVs Target Tracking and Cooperative Competition," IEEE/CAA J. Autom. Sinica, vol. 8, no. 12, pp. 1931-1947, Dec. 2021. doi: 10.1109/JAS.2020.1003012

An Optimal Control Strategy for Multi-UAVs Target Tracking and Cooperative Competition

doi: 10.1109/JAS.2020.1003012
Funds:  This work was supported by the National Natural Science Foundation of China (71462018, 71761018) and the Science and Technology Program of Education Department of Jiangxi Province in China (GJJ171503)
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  • An optimal control strategy of winner-take-all (WTA) model is proposed for target tracking and cooperative competition of multi-UAVs (unmanned aerial vehicles). In this model, firstly, based on the artificial potential field method, the artificial potential field function is improved and the fuzzy control decision is designed to realize the trajectory tracking of dynamic targets. Secondly, according to the finite-time convergence high-order differentiator, a double closed-loop UAV speed tracking the controller is designed to realize the speed control and tracking of the target tracking trajectory. Numerical simulation results show that the designed speed tracking controller has the advantages of fast tracking, high precision, strong stability and avoiding chattering. Finally, a cooperative competition scheme of multiple UAVs based on WTA is designed to find the minimum control energy from multiple UAVs and realize the optimal control strategy. Theoretical analysis and numerical simulation results show that the model has the fast convergence, high control accuracy, strong stability and good robustness.

     

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  • [1]
    E. Dun, B. Ferguson, and C. Beveridge, “Apical dominance and shoot branching. Divergent opinions or divergent mechanisms?” Plant Physiology, vol. 142, no. 3, pp. 812–819, 2006. doi: 10.1104/pp.106.086868
    [2]
    M. Enquist and S. Ghirlanda, Neural Networks and Animal Behavior. Princetion University Press, Princeton, USA. 2005.
    [3]
    S. Ottone and F. Ponzano, “Competition and cooperation in markets. The experimental case of a winners-take-all setting,” J. Socio-Economics, vol. 39, no. 2, pp. 163–170, 2010. doi: 10.1016/j.socec.2009.10.001
    [4]
    S. Li, Y. P. Wang, J. G. Yu, and B. Liu, “A nonlinear model to generate the Winners-take-all competition,” Communications in Nonlinear Science &Numerical Simulation, vol. 18, no. 3, pp. 435–442, 2013.
    [5]
    U. Rutishauser, R. J. Douglas, J. J. Slotine, “Collective stability of networks of winnertake-all circuits,” Neural Comput, vol. 23, no. 3, pp. 735–773, 2011.
    [6]
    S. Li, M. C. Zhou, X. Luo, and Z. H. You, “Distributed winners-take-all in dynamic networks,” IEEE Trans. Automatic Control, vol. 62, no. 2, pp. 577–589, 2017. doi: 10.1109/TAC.2016.2578645
    [7]
    S. Li, Y. M. Li, and Z. Wang, “A class of finite-time dual neural networks for solving quadratic programming problems and its winners-take-all application,” Neural Networks the Official J. the Int. Neural Network Society, vol. 39, pp. 27–39, 2013. doi: 10.1016/j.neunet.2012.12.009
    [8]
    H. Wang, Y. J. Huang, A. Khajepour, Y. B. Zhang, Y. Rasekhipour, and D. P. Cao, “Crash mitigation in motion planning for autonomous vehicles,” IEEE Trans. Intelligent Transportation Systems, vol. 20, no. 9, pp. 3313–3323, Sept. 2019. doi: 10.1109/TITS.2018.2873921
    [9]
    L. Cao, D. Qiao, and J. W. Xu, “Suboptimal artificial potential function sliding mode control for spacecraft rendezvous with obstacle avoidance,” Acta Astronautica, vol. 143, pp. 133–146, Feb. 2018. doi: 10.1016/j.actaastro.2017.11.022
    [10]
    Y. Liu, P. F. Huang, F. Zhang, and Y. K. Zhao, “Distributed formation control using artificial potentials and neural network for constrained multiagent systems,” IEEE Trans. Control Systems Technology, vol. 28, no. 2, pp. 697–704, Mar. 2019. doi: 10.1109/TCST.2018.2884226
    [11]
    S. M. H. Rostami, A. K. Sangaiah, J. Wang, and X. Z. Liu, “Obstacle avoidance of mobile robots using modified artificial potential field algorithm,” EURASIP J. Wireless Communications and Networking, 2019. DOI: 10.1186/s13638-019-1396-2
    [12]
    F. Zhou, Y. J. Zhou, G. P. Jiang, and N. Cao, “Adaptive tracking control of quadrotor UAV system with input constraints,” in Proc. 30th China Conf. Control and Decision-Making, pp. 5774–5779, Jun. 2018.
    [13]
    L. Qiao and W. D. Zhang, “Double-loop integral terminal sliding mode tracking control for UUVs with adaptive dynamic compensation of uncertainties and disturbances,” IEEE J. Oceanic Engineering, vol. 99, pp. 1–25, 2018.
    [14]
    Y. Zhang, Z. Q. Chen, X. H. Zhang, Q. L. Sun, and M. W. Sun, “A novel control scheme for quadrotor UAV based upon active disturbance rejection control,” Aerospace Science &Technology, vol. 79, pp. 601–609, Aug. 2018. doi: 10.1016/j.ast.2018.06.017
    [15]
    X. L. Shao, J. Liu, H. L. Cao, C. Shen, and H. L. Wang, “Robust dynamic surface trajectory tracking control for a quadrotor UAV via extended state observer,” Int. J. Robust &Nonlinear Control, vol. 28, no. 7, 2018.
    [16]
    J. M. C. Francisco, T. S. Jorge, C. R. Inmaculada, G. F. Alfonso, M. P. B. José, B. S. Irene, and L. G. Francisca, “Assessing optimal flight parameters for generating accurate multispectral orthomosaicks by UAV to support site-specific crop management,” Remote Sensing, vol. 7, no. 10, pp. 12793–12814, 2015. doi: 10.3390/rs71012793
    [17]
    R. Kikutis, J. Stankunas, D. Rudinskas, and T. Masiulionis, “Adaptation of dubins paths for uav ground obstacle avoidance when using a low cost on-board GNSS sensor,” Sensors, vol. 17, no. 10, Article No. 2223(1–23), 2017.
    [18]
    L. Sun and Z. W. Zheng, “Nonlinear adaptive trajectory tracking control for a stratospheric airship with parametric uncertainty,” Nonlinear Dynamics, vol. 82, no. 3, pp. 1–12, 2015.
    [19]
    F. Y. Chen, R. Q. Jiang, K. K. Zhang, and B. Jiang, “Robust backstepping sliding mode control and observer-based fault estimation for a quadrotor UAV,” IEEE Trans. Industrial Electronics, vol. 63, no. 8, pp. 1–12, 2016.
    [20]
    X. Fang, A. G. Wu, Y. J. Shang, and N. Dong, “A novel sliding mode controller for small-scale unmanned helicopters with mismatched disturbancel,” Nonlinear Dynamics, vol. 83, no. 1–2, pp. 1053–1068, Jan. 2016. doi: 10.1007/s11071-015-2387-4
    [21]
    K. P. Lin and K. C. Hung, “An efficient fuzzy weighted average algorithm for the military UAV selecting under group decision-making,” Knowledge-Based Systems, vol. 24, no. 6, pp. 877–889, 2011. doi: 10.1016/j.knosys.2011.04.002
    [22]
    J. Gomez and M. Jamshidi, “Fuzzy adaptive control for a UAV,” J. Intelligent &Robotic Systems, vol. 62, no. 2, pp. 271–293, 2011.
    [23]
    J. Azinheira and A. Moutinho, “Hover control of an UAV with backstepping design including input saturations,” IEEE Trans. Control Systems Technology, vol. 16, no. 3, pp. 517–526, 2008. doi: 10.1109/TCST.2007.908209
    [24]
    B. Zhao, B. Xian, Y. Zhang, and X. Zhang, “Nonlinear robust adaptive tracking control of a quadrotor UAV via immersion and invariance methodology,” IEEE Trans. Industrial Electronics, vol. 62, no. 5, pp. 2891–2902, 2015. doi: 10.1109/TIE.2014.2364982
    [25]
    B. Xian, C. Diao, B. Zhao, and Y. Zhang, “Nonlinear robust output feedback tracking control of a quadrotor UAV using quaternion representation,” Nonlinear Dynamics, vol. 79, no. 4, pp. 2735–2752, 2015. doi: 10.1007/s11071-014-1843-x
    [26]
    S. Li, B. Liu, and Y. M. Li, “Selective positive-negative feedback produces the winners-take-all competition in recurrent neural networks,” IEEE Trans. Neural Networks &Learning Systems, vol. 24, no. 2, pp. 301–309, 2013.
    [27]
    R. Xu and U. Ozguner, “Sliding mode control of a class of under actuated systems,” Automatica, vol. 44, no. 1, pp. 233–241, 2008. doi: 10.1016/j.automatica.2007.05.014
    [28]
    K. Passino and S. Yurkovich, Fuzzy Control. Tsinghua University Press., 2001.
    [29]
    J. Anagnost and C. Desoer, “An elementary proof of the Routh-Hurwitz stability criterion,” Circuits,Systems and Signal Processing, vol. 10, no. 1, pp. 101–114, 1991. doi: 10.1007/BF01183243
    [30]
    X. H. Wang and J. K. Liu, Differentiator Design and Application-Signal Filtering and Differentiation. Electronic Industry Press, China., pp. 60–71. 2010.
    [31]
    H. Khalil, “Nonlinear Systems Third Edition. Upper Saddle River, ” NJ: Prentice-Hall., 2002.
    [32]
    D. Q. Zhu and M. Z. Yan, “Survey on technology of mobile robot path planning,” Control and Decision, vol. 25, no. 7, pp. 961–967, 2010.
    [33]
    S. Bhat and D. Bernstein, “Continuous finite-time stabilization of the translational and rotational double integrators,” IEEE Trans. Autom. Control, vol. 43, no. 5, pp. 678–682, 1998. doi: 10.1109/9.668834
    [34]
    Y. G. Hong, “Finite-time stabilization and stabilizability of a class of controllable systems,” Systems &Control Letters, vol. 46, no. 4, pp. 231–236, 2002.
    [35]
    X. Q. Huang, W. Lin, and B. Yang, “Global finite-time stabilization of a class of uncertain nonlinear systems,” Automatica, vol. 41, no. 5, pp. 881–888, 2005. doi: 10.1016/j.automatica.2004.11.036
    [36]
    A. Levant, “Robust exact differentiation via sliding mode technique,” Automatica, vol. 34, no. 3, pp. 379–384, 1998. doi: 10.1016/S0005-1098(97)00209-4
    [37]
    H. Khalil, “Robust servomechanism output feedback controllers for feedback linearizable systems,” Automatica, vol. 30, no. 10, pp. 1587–1599, 1994. doi: 10.1016/0005-1098(94)90098-1

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    Highlights

    • An optimal control strategy of WTA model is proposed for target tracking and cooperative competition of multi-UAVs.
    • A double closed-loop UAV speed tracking the controller is designed.
    • A trajectory tracking method of dynamic target is designed.

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