Abstract
This paper discusses the uncooperative target tracking control problem for the unmanned aerial vehicle (UAV) under the performance constraint and scaled relative velocity constraint, in which the states of the uncooperative target can only be estimated through a vision sensor. Considering the limited detection range, a prescribed performance function is designed to ensure the transient and steady-state performances of the tracking system. Meanwhile, the scaled relative velocity constraint in the dynamic phase is taken into account, and a time-varying nonlinear transformation is used to solve the constraint problem, which not only overcomes the feasibility condition but also fails to violate the constraint boundaries. Finally, the practically prescribed-time stability technique is incorporated into the controller design procedure to guarantee that all signals within the closed-loop system are bounded. It is proved that the UAV can follow the uncooperative target at the desired relative position within a prescribed time, thereby improving the applicability of the vision-based tracking approach. Simulation results have been presented to prove the validity of the proposed control strategy.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Ren W and Beard R W, Trajectory tracking for unmanned air vehicles with velocity and heading rate constraints, IEEE Transactions on Control Systems Technology, 2004, 12(5): 706–716.
Wang Y, Wang X, Zhao S, et al., Vector field based sliding mode control of curved path following for miniature unmanned aerial vehicles in winds, Journal of Systems Science & Complexity, 2018, 31(1): 302–324.
Ren H R, Ma H, Li H Y, et al., Adaptive fixed-time control of nonlinear MASs with actuator faults, IEEE/CAA Journal of Automatica Sinica, 2023, 10(5): 1252–1262.
Zheng X H, Li H Y, Ahn C K, et al., Observer-based finite-time consensus control for multiagent systems with nonlinear faults, Information Sciences, 2023, 621: 183–199.
Nocerino A, Opromolla R, Fasano G, et al., Lidar-based multi-step approach for relative state and inertia parameters determination of an uncooperative target, Acta Astronautica, 2021, 181: 662–678.
Stepanyan V and Hovakimyan N, Visual tracking of a maneuvering target, Journal of Guidance, Control, and Dynamics, 2008, 31(1): 66–80.
Zheng W, Zhou F, and Wang Z F, Robust and accurate monocular visual navigation combining IMU for a quadrotor, IEEE/CAA Journal of Automatica Sinica, 2015, 2(1): 33–44.
Liang J C, Chen Y J, Wu Y N, et al., Adaptive prescribed performance control of unmanned aerial manipulator with disturbances, IEEE Transactions on Automation Science and Engineering, 2023, 20: 1804–1814.
Chen G D, Liu Y, Yao D Y, et al., Event-triggered tracking control of nonlinear systems under sparse attacks and its application to rigid aircraft, IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(4): 4640–4650.
Liu Y, Chi R H, Li H Y, et al., HiTL-based adaptive fuzzy tracking control of MASs: A distributed fixed-time strategy, Science China Technological Sciences, 2023, 66: 2907–2916.
Gao H J, An H, Lin W Y, et al., Trajectory tracking of variable centroid objects based on fusion of vision and force perception, IEEE Transactions on Cybernetics, 2023, 53(12): 7957–7965.
Zhang L L, Deng F, Chen J, et al., Vision-based target three-dimensional geolocation using unmanned aerial vehicles, IEEE Transactions on Industrial Electronics, 2018, 65(10): 8052–8061.
Lai N B, Chen Y J, Liang J C, et al., Image dynamics-based visual servo control for unmanned aerial manipulatorl with a virtual camera, IEEE-ASME Transactions on Mechatronics, 2022, 27(6): 5264–5274.
Zhang J, Wu Y, Liu W, et al., Novel approach to position and orientation estimation in vision-based UAV navigation, IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(2): 687–700.
Jabbari A H and Yoon J, Robust image-based control of the quadrotor unmanned aerial vehicle, Nonlinear Dynamics, 2016, 85(3): 2035–2048.
Segal S, Carmi A, and Gurfil P, Stereovision-based estimation of relative dynamics between noncooperative satellites: Theory and experiments, IEEE Transactions on Control Systems Technology, 2013, 22(2): 568–584.
Yu Z Q, Liu Z X, Zhang Y M, et al., Distributed finite-time fault-tolerant containment control for multiple unmanned aerial vehicles, IEEE Transactions on Neural Networks and Learning Systems, 2019, 31(6): 2077–2091.
Sun P, Zhu B, Zuo Z Y, et al., Vision-based finite-time uncooperative target tracking for UAV subject to actuator saturation, Automatica, 2021, 130: 109708.
Zuo Z Y, Han Q L, Ning B D, et al., An overview of recent advances in fixed-time cooperative control of multiagent systems, IEEE Transactions on Industrial Informatics, 2018, 14(6): 2322–2334.
Jiménez-Rodríguez E, Muñoz-Vázquez A J, Sánchez-Torres J D, et al., A Lyapunov-like characterization of predefined-time stability, IEEE Transactions on Automatic Control, 2020, 65(11): 4922–4927.
Song Y D, Wang Y J, Holloway J, et al., Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time, Automatica, 2017, 83: 243–251.
Becerra H M, Vázquez C R, Arechavaleta G, et al., Predefined-time convergence control for high-order integrator systems using time base generators, IEEE Transactions on Control Systems Technology, 2017, 26(5): 1866–1873.
Shao K and Zheng J C, Predefined-time sliding mode control with prescribed convergent region, IEEE/CAA Journal of Automatica Sinica, 2022, 9(5): 934–936.
Bechlioulis C P and Rovithakis G A, Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance, IEEE Transactions on Automatic Control, 2008, 53(9): 2090–2099.
Xin B, Cheng S, Wang Q, et al., Fixed-time prescribed performance consensus control for multi-agent systems with non-affine faults, IEEE Transactions on Fuzzy Systems, 2023, 31(10): 3433–3446.
Zheng X H, Ma H, Yao D Y, et al., Neural-based predefined-time distributed optimization of high-order nonlinear multiagent systems, IEEE Transactions on Artificial Intelligence, 2023, DOI: https://doi.org/10.1109/TAI.2023.3343684.
Li Z, Zhang Y, and Zhang R, Prescribed error performance control for second-order fully actuated systems, Journal of Systems Science & Complexity, 2022, 35(2): 660–669.
Zhang L L, Che W W, Chen B, et al., Adaptive fuzzy output-feedback consensus tracking control of nonlinear multiagent systems in prescribed performance, IEEE Transactions on Cybernetics, 2022, 53(3): 1932–1943.
Ma H, Zhou Q, Li H, et al., Adaptive prescribed performance control of a flexible-joint robotic manipulator with dynamic uncertainties, IEEE Transactions on Cybernetics, 2021, 52(12): 12905–12915.
Zhang F K, Wu W M, and Wang C, Pattern-based learning and control of nonlinear pure-feedback systems with prescribed performance, Science China Information Sciences, 2023, 66(1): 112202.
Berger T, Le H H, and Reis T, Funnel control for nonlinear systems with known strict relative degree, Automatica, 2018, 87: 345–357.
Li Y F, Park J H, Hua C C, et al., Global output feedback tracking control for switched nonlinear systems with deferred prescribed performance, Journal of the Franklin Institute, 2021, 358(3): 1743–1764.
Zhao K, Song Y D, Chen C L P, et al., Adaptive asymptotic tracking with global performance for nonlinear systems with unknown control directions, IEEE Transactions on Automatic Control, 2021, 67(3): 1566–1573.
Wu J, He F R, Shen H, et al., Adaptive NN fixed-time fault-tolerant control for uncertain stochastic system with deferred output constraint via self-triggered mechanism, IEEE Transactions on Cybernetics, 2023, 53(9): 5892–5903.
Zhang H Y, Zhao X D, Wang H Q, et al., Adaptive tracking control for output-constrained switched MIMO pure-feedback nonlinear systems with input saturation, Journal of Systems Science & Complexity, 2023, 36(3): 960–984.
He H F, Qi W H, Yan H C, et al., Adaptive fuzzy resilient control for switched systems with state constraints under deception attacks, Information Sciences, 2023, 621: 596–610.
Ma H, Ren H R, Zhou Q, et al., Observer-based neural control of n-link flexible-joint robots, IEEE Transactions on Neural Networks and Learning Systems, 2022, DOI: https://doi.org/10.1109/TNNLS.2022.3203074.
Niu B, Wang X A, Wang X M, et al., Adaptive Barrier-Lyapunov-functions based control scheme of nonlinear pure-feedback systems with full state constraints and asymptotic tracking performance, Journal of Systems Science & Complexity, 2024, 37(3): 965–984.
Liu L, Gao T T, Liu Y J, et al., Time-varying IBLFs-based adaptive control of uncertain nonlinear systems with full state constraints, Automatica, 2021, 129: 109595.
Yu J P, Zhao L, Yu H S, et al., Barrier Lyapunov functions-based command filtered output feedback control for full-state constrained nonlinear systems, Automatica, 2019, 105: 71–79.
Zhao K, Song Y D, and Zhang Z R, Tracking control of MIMO nonlinear systems under full state constraints: A single-parameter adaptation approach free from feasibility conditions, Automatica, 2019, 107: 52–60.
Guo C, Xie X J, and Hou Z G, Removing feasibility conditions on adaptive neural tracking control of nonlinear time-delay systems with time-varying powers, input, and full-state constraints, IEEE Transactions on Cybernetics, 2020, 52(4): 2553–2564.
Shi X C, Xu S Y, Jia X L, et al., Adaptive neural control of state-constrained MIMO nonlinear systems with unmodeled dynamics, Nonlinear Dynamics, 2022, 108: 4005–4020.
Huang Y and Jia Y M, Adaptive fixed-time six-DOF tracking control for noncooperative spacecraft fly-around mission, IEEE Transactions on Control Systems Technology, 2018, 27(4): 1796–1804.
She X H, Li X M, Yao D Y, et al., Vision-based adaptive fixed-time uncooperative target tracking for QUAV with unknown disturbances, Journal of the Franklin Institute, 2023, 360(16): 12394–12414.
Pan Y N, Ji W Y, Lam H K, et al., An improved predefined-time adaptive neural control approach for nonlinear multiagent systems, IEEE Transactions on Automation Science and Engineering, 2023, DOI: https://doi.org/10.1109/TASE.2023.3324397.
Xiong J J and Zheng E H, Position and attitude tracking control for a quadrotor UAV, ISA Transactions, 2014, 53(3): 725–731.
Yao D Y, Li H Y, and Shi Y, Adaptive event-triggered sliding mode control for consensus tracking of nonlinear multi-agent systems with unknown perturbations, IEEE Transactions on Cybernetics, 2023, 53(4): 2672–2684.
Wang Z W, Liang B, Sun Y C, et al., Adaptive fault-tolerant prescribed-time control for teleoperation systems with position error constraints, IEEE Transactions on Industrial Informatics, 2019, 16(7): 4889–4899.
Sun J Y, Zhang H G, Wang Y C, et al., Fault-tolerant control for stochastic switched IT2 fuzzy uncertain time-delayed nonlinear systems, IEEE Transactions on Cybernetics, 2020, 52(2): 1335–1346.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
LI Hongyi is an editorial board member for Journal of Systems Science & Complexity and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.
Additional information
This work was partially supported by the National Natural Science Foundation of China under Grant Nos. 62033003, 62203119, 62373113, U23A20341, and U21A20522, and the Natural Science Foundation of Guangdong Province under Grant Nos. 2023A1515011527 and 2022A1515011506.
This paper was recommended for publication by Editor SUN Jian.
Rights and permissions
About this article
Cite this article
She, X., Ma, H., Ren, H. et al. Vision-Based Adaptive Prescribed-Time Control of UAV for Uncooperative Target Tracking with Performance Constraint. J Syst Sci Complex 37, 1956–1977 (2024). https://doi.org/10.1007/s11424-024-3443-2
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-024-3443-2