带有输出约束的水面船舶实际有限时间控制

考虑带有输出约束的水面船舶系统,提出一种自适应神经网络航迹跟踪实际有限时间控制算法.基于反步法设计有限时间控制律,构造障碍李雅普诺夫函数处理输出约束问题,采用神经网络逼近船舶模型中的不确定信息.在控制算法递推过程中,通过设计一个关于跟踪误差的可微幂函数来避免控制器中的奇异问题.借助李雅普诺夫稳定性分析理论,证明了航迹跟踪误差在有限时间内收敛到有界的邻域内.最后,以一艘1:70的比例模型船作为仿真对象,来验证所提出的航迹跟踪实际有限时间控制算法的有效性.

Practical finite-time control for marine surface vessel with output constraints

This paper presents an adaptive neural network trajectory tracking control scheme for a marine surface vehicle with output constraints. The finite-time control law is designed by the virtue of backstepping technique. The barrier Lyapunov functions are constructed to address the output constraints problem. The neural networks are adopted to approximate model uncertainties of the marine surface vehicle. In the recursively design process, a differentiable power function of tracking error is designed to avoid the singularity problem. By means of the Lyapunov stability analysis theory, the trajectory tracking error can converge to a bounded neighbourhood in finite time. Finally, a 1: 70 scale replica of supply ship is used as a simulation object to illustrate the validity of the presented trajectory tracking practical finite time control method.