Accurate track control of unmanned underwater vehicle under complex disturbances
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摘要:
目的 针对外界复杂干扰下水下机器人三维轨迹精确跟踪控制的问题,提出一种基于有限时间扰动观测器的非奇异终端滑模控制方法。 方法 设计非奇异终端滑模轨迹跟踪控制器,保证跟踪误差在有限时间内精确收敛到零。在外界多维度时变干扰下,设计有限时间扰动观测器,提高系统的抗干扰能力。 结果 利用Lyapunov函数证明所设计控制策略可以有限时间稳定。采用MATLAB进行仿真实验,在阶跃扰动下与反步滑模控制方法仿真对比,表明所提方法可实现轨迹的精确跟踪。 结论 研究结果可为水下机器人的三维轨迹精确跟踪提供解决思路。 Abstract:Objectives This paper presents a non-singular terminal sliding mode track control method based on a finite-time disturbance observer to solve the problem of accurately tracking and controlling an the 3D trajectory of an unmanned underwater vehicle under complex external disturbances. Methods A non-singular terminal sliding mode track controller is designed to ensure that the tracking error converges to zero accurately within a limited time. A finite-time disturbance observer is designed to improve the anti-jamming ability of the system under external multidimensional time-varying disturbances. Results The Lyapunov function is used to prove that the designed control strategy can remain stable for a limited time. MATLAB is used for the simulation experiment, and a comparison with the backstepping sliding mode control method under step disturbance shows that the method presented in this paper achieves accurate trajectory tracking. Conclusions The results of this paper can provide a solution for accurately tracking the 3D trajectories of unmanned underwater vehicles. -
表 1 三种方法的性能比较
Table 1. Performance comparison of three methods
性能指标 FDO-NTSMC BSMC NTSMC IAE $ {x_{\text{e}}} $ 0.462 7 1.061 0 1.265 8 $ {y_{\text{e}}} $ 0.356 2 0.766 6 1.603 3 $ {z_{\text{e}}} $ 0.395 6 0.528 4 2.460 3 $ {\theta _{\text{e}}} $ 1.593 2 2.050 1 2.326 6 $ {\psi _{\text{e}}} $ 2.656 4 2.848 2 4.142 3 ITAE $ {x_{\text{e}}} $ 0.561 2 24.282 7 33.159 9 $ {y_{\text{e}}} $ 0.292 6 11.964 8 51.427 9 $ {z_{\text{e}}} $ 0.460 6 7.384 6 80.571 9 $ {\theta _{\text{e}}} $ 1.779 8 16.042 0 16.232 8 $ {\psi _{\text{e}}} $ 3.749 6 17.936 6 39.832 9 表 2 阶跃扰动下3种方法性能比较
Table 2. Performance comparison of three methods under step perturbation
性能指标 FDO-NTSMC BSMC NTSMC IAE $ {x_{\text{e}}} $ 0.626 5 1.718 2 5.916 2 $ {y_{\text{e}}} $ 0.513 5 1.456 3 6.499 6 $ {z_{\text{e}}} $ 0.555 3 1.234 4 7.711 7 $ {\theta _{\text{e}}} $ 1.740 6 2.576 4 5.167 5 $ {\psi _{\text{e}}} $ 2.820 2 3.520 0 8.959 2 ITAE $ {x_{\text{e}}} $ 6.568 8 48.180 9 203.403 5 $ {y_{\text{e}}} $ 5.986 0 37.016 3 231.457 9 $ {z_{\text{e}}} $ 6.288 3 33.114 5 272.619 8 $ {\theta _{\text{e}}} $ 7.129 9 35.028 3 85.621 4 $ {\psi _{\text{e}}} $ 9.733 6 42.372 9 213.641 1 表 3 执行器限幅下3种方法性能比较
Table 3. Performance comparison of three methods under the condition of limiting amplitude of control input
性能指标 FDO-NTSMC BSMC NTSMC IAE $ {x_{\text{e}}} $ 0.466 3 0.940 9 1.767 4 $ {y_{\text{e}}} $ 0.381 3 0.815 4 2.326 4 $ {z_{\text{e}}} $ 0.437 5 0.641 1 3.513 0 $ {\theta _{\text{e}}} $ 1.593 2 2.050 1 3.422 3 $ {\psi _{\text{e}}} $ 1.994 5 1.690 2 3.192 1 ITAE $ {x_{\text{e}}} $ 0.567 2 19.343 2 52.946 8 $ {y_{\text{e}}} $ 0.322 0 11.429 8 80.644 2 $ {z_{\text{e}}} $ 0.528 2 7.112 8 119.339 1 $ {\theta _{\text{e}}} $ 1.779 8 16.042 0 23.617 4 $ {\psi _{\text{e}}} $ 2.423 6 14.800 6 56.396 3 -
[1] XIANG X B, LAPIERRE L, JOUVENCEL B. Smooth transition of AUV motion control: from fully-actuated to under-actuated configuration[J]. Robotics and Autonomous Systems, 2015, 67: 14–22. [2] SANTHAKUMAR M, ASOKAN T. Power efficient dynamic station keeping control of a flat-fish type autonomous underwater vehicle through design modifications of thruster configuration[J]. Ocean Engineering, 2013, 58: 11–21. [3] LI H P, YAN W S. Model predictive stabilization of constrained underactuated autonomous underwater vehicles with guaranteed feasibility and stability[J]. IEEE/ASME Transactions on Mechatronics, 2017, 22(3): 1185–1194. [4] SHEN C, SHI Y. Distributed implementation of nonlinear model predictive control for AUV trajectory tracking[J]. Automatica, 2020, 115: 108863. [5] QIAO L, ZHANG W D. Double-loop integral terminal sliding mode tracking control for UUVs with adaptive dynamic compensation of uncertainties and disturbances[J]. IEEE Journal of Oceanic Engineering, 2019, 44(1): 29–53. [6] 王芳, 万磊, 李晔, 等. 欠驱动AUV的运动控制技术综述[J]. 中国造船, 2010, 51(2): 227–241. doi: 10.3969/j.issn.1000-4882.2010.02.030WANG F, WAN L, LI Y, et al. A survey on development of motion control for underactuated AUV[J]. Shipbuilding of China, 2010, 51(2): 227–241 (in Chinese). doi: 10.3969/j.issn.1000-4882.2010.02.030 [7] QIAO L, ZHANG W D. Double-loop chattering-free adaptive integral sliding mode control for underwater vehicles[C]//OCEANS 2016-Shanghai. Shanghai: IEEE, 2016: 1-6. [8] REZAZADEGAN F, SHOJAEI K, SHEIKHOLESLAM F, et al. A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties[J]. Ocean Engineering, 2015, 107: 246–258. [9] GUERRERO J, TORRES J, CREUZE V, et al. Trajectory tracking for autonomous underwater vehicle: an adaptive approach[J]. Ocean Engineering, 2019, 172: 511–522. [10] QIAO L, ZHANG W D. Adaptive non-singular integral terminal sliding mode tracking control for autonomous underwater vehicles[J]. IET Control Theory & Applications, 2017, 11(8): 1293–1306. [11] 孙巧梅, 陈金国, 余万. 水下航行器三维航迹反演滑模跟踪控制[J]. 舰船科学技术, 2019, 41(1): 66–70. doi: 10.3404/j.issn.1672-7649.2019.01.012SUN Q M, CHEN J G, YU W. 3D trajectory-tracking control of autonomous underwater vehicles based on backstepping and sliding mode method[J]. Ship Science and Technology, 2019, 41(1): 66–70 (in Chinese). doi: 10.3404/j.issn.1672-7649.2019.01.012 [12] 魏斯行, 刘晗, 马宁, 等. 基于反步控制和神经动力学模型的带缆水下潜器航迹跟踪[J]. 舰船科学技术, 2020, 42(1): 88–94. doi: 10.3404/j.issn.1672-7649.2020.01.018WEI S H, LIU H, MA N, et al. Tracking control for tethered underwater vehicle based on backstepping mode and neurodynamics model[J]. Ship Science and Technology, 2020, 42(1): 88–94 (in Chinese). doi: 10.3404/j.issn.1672-7649.2020.01.018 [13] 张伟, 滕延斌, 魏世琳, 等. 欠驱动UUV自适应RBF神经网络反步跟踪控制[J]. 哈尔滨工程大学学报, 2018, 39(1): 93–99.ZHANG W, TENG Y B, WEI S L, et al. Underactuated UUV tracking control of adaptive RBF neural network and backstepping method[J]. Journal of Harbin Engineering University, 2018, 39(1): 93–99 (in Chinese). [14] 严浙平, 段海璞. UUV航迹跟踪的双闭环Terminal滑模控制[J]. 中国舰船研究, 2015, 10(4): 112–117, 142. doi: 10.3969/j.issn.1673-3185.2015.04.017YAN Z P, DUAN H P. A double closed-loop Terminal sliding mode controller for the trajectory tracking of UUV[J]. Chinese Journal of Ship Research, 2015, 10(4): 112–117, 142 (in Chinese). doi: 10.3969/j.issn.1673-3185.2015.04.017 [15] WANG N, KARIMI H R. Successive waypoints tracking of an underactuated surface vehicle[J]. IEEE Transactions on Industrial Informatics, 2020, 16(2): 898–908. [16] WANG N, HE H K. Dynamics-level finite-time fuzzy monocular visual servo of an unmanned surface vehicle[J]. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9648–9658. [17] 邓琪. 四旋翼飞行器高精度跟踪控制研究[D]. 大连: 大连海事大学, 2019.DENG Q. High-precision tracking control of a quadrotor aircraft[D]. Dalian: Dalian Maritime University, 2019 (in Chinese). [18] BHAT S P, BERNSTEIN D S. Finite-time stability of homogeneous systems[C]//Proceedings of the 1997 American Control Conference (Cat. No. 97CH36041). Albuquerque: IEEE, 1997: 2513-2514. [19] SHTESSEL Y B, SHKOLNIKOV I A, LEVANT A. Smooth second-order sliding modes: missile guidance application[J]. Automatica, 2007, 43(8): 1470–1476. [20] FOSSEN T I. Guidance and control of ocean vehicles[M]. Chichester: Wiley, 1994. [21] FENG Y, YU X H, MAN Z H. Non-singular terminal sliding mode control of rigid manipulators[J]. Automatica, 2002, 38(12): 2159–2167. [22] 梁松. 水下检测与作业机器人ROV控制系统研制及动力定位研究[D]. 镇江: 江苏科技大学, 2017.LIANG S. Research on the control system development and dynamic positioning of underwater detection and operation ROV[D]. Zhenjiang: Jiangsu University of Science and Technology, 2017 (in Chinese). [23] WANG N, HE H K. Extreme learning-based monocular visual servo of an unmanned surface vessel[J]. IEEE Transactions on Industrial Informatics, 2020. doi: 10.1109/TII.2020.3033794. [24] WANG N, SU S F. Finite-time unknown observer-based interactive trajectory tracking control of asymmetric underactuated surface vehicles[J]. IEEE Transactions on Control Systems Technology, 2021, 29(2): 794–803. [25] WANG N, Er M J. Self-constructing adaptive robust fuzzy neural tracking control of surface vehicles with uncertainties and unknown disturbances[J]. IEEE Transactions on Control Systems Technology, 2015, 23(3): 991–1002. [26] WANG N, DENG Q, XIE G M, et al. Hybrid finite-time trajectory tracking control of a quadrotor[J]. ISA Transactions, 2019, 90: 278–286. -
ZG2236_en.pdf
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