具有输入时滞约束的氢电无人船路径跟踪控制

Path-following control of hydrogen-powered unmanned surface vehicles with input-delay constrains

  • 摘要: 【目的】针对氢燃料电池动力欠驱动无人船的输入时滞问题,研究对应的路径跟踪控制方法,解决传统策略跟踪精度低、稳定性差的问题。【方法】引入纵荡视线制导算法同步规划纵荡速度与艏摇角;构造二阶辅助动力学系统将含1-3秒输入时滞的无人船模型转化为无时滞系统,结合坐标变换与反步法设计纵向、艏向反馈控制器,构建基于辅助系统的路径跟踪控制方案;以CybershipⅠ为平台开展对比仿真验证。【结果】所提制导算法实现路径跟踪误差渐近收敛,收敛速度与精度均优于 ILOS、ALOS 算法;所提控制方案有效补偿输入时滞,相较无滞补偿方案,跟踪无抖动、稳态误差更低,控制输入更平滑,辅助系统状态变量可快速收敛。【结论】纵荡视线制导算法可提升无人船运动学跟踪性能,二阶辅助系统能有效补偿氢电系统输入时滞,所提控制方案可显著提升输入时滞约束下氢电无人船路径跟踪的精度、响应速度与鲁棒性,为该类无人船控制提供有效方案。

     

    Abstract: Objectives Aiming at the input delay problem of underactuated unmanned surface vehicles (USVs) powered by hydrogen fuel cells, the study is conducted to propose a feasible path-following control method to improve the control performance of such USVs under input delay constraints. Methods First, the surge-guided line-of-sight (SGLOS) guidance algorithm was introduced to synchronously plan the surge speed and yaw angle at the kinematic level, so as to realize the asymptotic convergence of path-following errors. Second, a second-order auxiliary dynamic system was constructed to transform the USV model with 1-3 s input delay into a delay-free nonlinear dynamic system. Then, the backstepping method combined with coordinate transformation was adopted to design the longitudinal and heading feedback controllers respectively, and the auxiliary system-based path following control (AS-PFC) scheme was constructed. Finally, comparative simulations were carried out on the Cybership Ⅰ platform, in which the SGLOS algorithm was compared with ILOS and ALOS algorithms, and the AS-PFC scheme was compared with the robust path-following control scheme without delay compensation. Results The SGLOS algorithm showed better performance in convergence speed, tracking smoothness and steady-state error than ILOS and ALOS algorithms at the kinematic level. The AS-PFC scheme effectively compensated the 1-3 s input delay, which realized faster and smoother path-following convergence, reduced steady-state error, and generated control inputs with smaller amplitude and smoother variation; the state variables of the auxiliary system converged rapidly, and all signals of the closed-loop system kept uniformly ultimately bounded. Conclusions The SGLOS guidance algorithm can effectively improve the kinematic path-following performance of underactuated USVs. The second-order auxiliary dynamic system can well compensate the input delay caused by hydrogen fuel cell systems, and the designed AS-PFC scheme significantly improves the path-following accuracy, response speed and robustness of hydrogen-powered USVs under input delay constraints, providing an effective technical solution for the path-following control of such USVs.

     

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