路径跟踪控制是无人艇自主回收的关键技术之一，无人艇回收过程中航速慢、舵效差，不仅易受外界环境干扰，而且受执行机构限制，控制输入易饱和，如不加以抑制会大幅降低无人艇回收对接成功率。针对以上问题，基于自适应ILOS导引策略，设计了无人艇鲁棒性回收路径跟踪控制器。为提高无人艇回收过程路径跟踪响应速度，将前视距离与横向位置跟踪误差相联系，设计了时变前视距离的自适应ILOS导引方法。考虑无人艇回收过程环境扰动未知，设计了指数收敛的扰动观测器，而后基于反步法设计了首向控制器与速度控制器，为克服反步法解析导数求解的弊端，设计了二阶滤波器实现了期望首向一阶导数和二阶导数的滤波估计。考虑无人艇回收过程控制输入易饱和，设计了饱和补偿辅助系统。在直线路径与曲线路径2种工况下，分别进行仿真对比试验，验证了算法的有效性与优越性。
Path following control is one of the key technologies for autonomous recovery of unmanned surface vehicles (USV). The slow speed and poor rudder efficiency during recovery of USV are not only susceptible to external environmental interference, but also limited by the actuator, and the control input is easy to saturate, which will significantly reduce the recovery docking success rate of USV if not suppressed. In response to the above problems, a robust recovery path following controller for USV is designed based on the adaptive ILOS guidance strategy. To improve the USV recovery process path following response speed, the adaptive ILOS guidance method with time-varying foresight distance is designed by linking the foresight distance to the lateral position following error. Considering the unknown environmental disturbance of USV recovery process, an exponentially convergent disturbance observer is designed, and then the bow controller and velocity controller are designed based on the backstepping method. To overcome the drawback of the analytical derivative solution of the backstepping method, a second-order filter is designed to realize the filter estimation of the expected bow first-order derivative and second-order derivative. Considering that the control input of USV recovery process is easy to saturate, a saturation compensation auxiliary system is designed. Simulation and comparison tests are carried out under two working conditions, linear path and curved path, to verify the effectiveness and superiority of the algorithm.
2023,45(21): 86-92 收稿日期：2022-12-2
DOI：10.3404/j.issn.1672-7649.2023.21.016
分类号：TP273
作者简介：许晨（1998-），男，硕士研究生，研究方向为无人艇导航与控制
参考文献：
[1] 胡常青, 朱玮, 何远清, 等. 无人水面艇自主导航技术[J]. 导航与控制, 2019, 18(1): 19-26.
[2] 张晓东, 刘世亮, 刘宇, 等. 无人水面艇收放技术发展趋势探讨[J]. 中国舰船研究, 2018, 13(6): 50-57.
[3] VOLDEN Ø, STAHL A, FOSSEN T I. Vision-based positioning system for auto-docking of unmanned surface vehicles[J]. International Journal of Intelligent Robotics and Applications, 2021.
[4] Yu W Y, Wang J, Tang G Y, et al. Dual-attention-based optical terminal guidance for the recovery of unmanned surface vehicles[J]. Ocean Engineering, 2021, 239: 109852.
[5] LEKKAS A M, FOSSEN T I. Integral LOS Path Following for curved paths based on a monotone cubic hermite spline parametrization[J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2014, 22(6): 2287-2300.
[6] 黄宏赟. 欠驱动无人船路径跟踪控制研究[D]. 大连: 大连海事大学, 2020.
[7] 陈霄, 刘忠, 张建强, 等. 基于改进积分视线导引策略的欠驱动无人水面艇路径跟踪[J]. 北京航空航天大学学报, 2018, 44(3): 489-498.
[8] 周利. 基于扰动补偿的无人艇路径跟踪控制算法研究[D]. 哈尔滨工程大学, 2018.
