负浮力四倾转推进器水下机器人（NQTAUV）的姿态控制受到各种干扰的影响，导致姿态跟踪误差。为了实现干扰的估计与补偿，进行精确的姿态跟踪，设计干扰观测器和姿态控制器。首先，建立姿态跟踪误差模型，基于抗干扰控制理论，设计干扰观测器估计干扰，然后设计姿态跟踪控制器，并在三自由度实验平台上进行姿态跟踪实验。比较干扰观测器激活和关闭情况下，跟踪正弦信号的性能。实验结果表明，干扰观测器能够准确估计干扰，控制器能够对干扰进行补偿，实现了高精度的姿态跟踪。研究结果显示，基于干扰观测器的姿态跟踪控制能够对干扰进行补偿，提高了姿态跟踪精度。
The attitude tracking control of negative-buoyancy quad tilt-rotor autonomous underwater vehicle (NQTAUV) is influenced by many disturbances, which results in the attitude tracking error. A disturbance observer and an attitude tracking controller are designed to estimate the disturbance and compensate it for high attitude tracking performance. The attitude tracking error model is derived, a disturbance observer is designed to estimate the disturbance, an attitude tracking controller is designed to track the target attitude under disturbance, the performance of the controller is validated by experiments. The experiments show that the estimation of the disturbance is near the real value, and precise attitude tracking is achieved. The research shows that the disturbance observer based attitude control can compensate the disturbance and improve the attitude tracking accuracy.
2020,42(2): 98-102 收稿日期：2018-11-30
DOI：10.3404/j.issn.1672-7649.2020.02.019
分类号：U674.941
基金项目：国家重点研发计划专项资助（2016YFC0300700）
作者简介：王涛(1986-),男,博士研究生,主要从事水下机器人运动控制、非线性系统、计算机视觉研究
参考文献：
[1] FOSSEN, T. Guidance and control of ocean vehicles[M]. John Willey & Sons:1994.
[2] BROWN, C. L. In Deep sea mining and robotics:Assessing legal, societal and ethical implications[C]//2017 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Austin, TX, USA, 2017:1-2.
[3] LI Y, PAN D, ZHAO Q, et al. Hydrodynamic performance of an autonomous underwater glider with a pair of bioinspired hydro wings-a numerical investigation[J]. Ocean Engineering, 2018, 163:51-57
[4] WYNN R B, HUVENNE V A I, LE BAS T P, et al. Autonomous underwater vehicles (auvs):Their past, present and future contributions to the advancement of marine geoscience[J]. Marine Geology, 2014, 352:451-468
[5] WANG T, WU C, WANG J, et al. Modeling and control of negative-buoyancy tri-tilt-rotor autonomous underwater vehicles based on immersion and invariance methodology[J]. Applied Sciences, 2018, 8
[6] HUI Y, TONG G, JIA-WANG L, et al. In Prediction of mode and static stability of negative buoyancy vehicle[C]//2011 Chinese Control and Decision Conference (CCDC), 2011:1903-1909.
[7] WU N, WU C, GE, T, et al. Pitch channel control of a remus auv with input saturation and coupling disturbances[J]. Applied Sciences, 2018, 8
[8] XIANG X, 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
[9] LI X, ZHAO M, GE T. A nonlinear observer for remotely operated vehicles with cable effect in ocean currents[J]. Applied Sciences, 2018, 8
[10] YUAN Y, YU Y, GUO L. Nonlinear active disturbance rejection control for the pneumatic muscle actuators with discrete-time measurements[J]. Ieee Transactions on Industrial Electronics, 2019, 66:2044-2053
[11] CUI R, YANG C, LI Y, SHARMA S. Adaptive neural network control of auvs with control input nonlinearities using reinforcement learning[J]. Ieee Transactions on Systems Man Cybernetics-Systems, 2017, 47:1019-1029
[12] LIU C, MCAREE O, CHEN W H. Path following for small uavs in the presence of wind disturbance, Control[C]//(Control), 2012 UKACC International Conference on, Cardiff, UK, 2012:613-618.
[13] PALOMERAS N, VALLICROSA G, MALLIOS A, et al. Auv homing and docking for remote operations[J]. Ocean Engineering, 2018, 154:106-120
[14] XING G Q, SHABBIR A P. Alternate forms of relative attitude kinematics and dynamics equations[C]//2001 Flight Mechanics Symposium, Greenbelt, MD, USA, 2001:83-97.
