Traffic engineering control is a major challenge in marine transportation. Cost efficiency and high performance demand advanced technologies for the ship control systems. This paper develops an autopilot heading control scheme based on a fuzzy state observer for an intelligent ship on this subject to track the prescribed function while calling for performance limitation and order execution time. A fuzzy logic system (FLS) is adopted to approximate the unknown uncertainties caused by the changes in water depth, wind, wave, ship loading, and speed in navigation. State observer is required to obtain unknown yaw rate. By adopting performance function and tracking error transformation techniques, the heading tracking error can converge to prescribed performance bounds. Taking settling time into account, the finite-time adaptive prescribed performance control algorithm can save more resources effectively. Based on the Lyapunov stability theory, the observer-based adaptive fuzzy control approach does not cause any unbounded signal, the system remains stable. Meanwhile, the autopilot heading control system with an unknown yaw rate and constraint state can benefit from the given design.

中文翻译：

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基于观测器的具有规定性能的智能船舶自动舵航向有限时间控制设计

交通工程控制是海上运输的一大挑战。成本效益和高性能要求船舶控制系统采用先进技术。本文开发了一种基于模糊状态观察器的自动驾驶仪航向控制方案，用于智能船舶在此主题上跟踪规定的功能，同时要求性能限制和命令执行时间。采用模糊逻辑系统（FLS）来逼近航行中水深、风、浪、船载和速度变化引起的未知不确定性。需要状态观察员来获得未知的偏航率。通过采用性能函数和跟踪误差变换技术，航向跟踪误差可以收敛到规定的性能界限。考虑到稳定时间，有限时间自适应指定性能控制算法可以有效地节省更多资源。基于李雅普诺夫稳定性理论，基于观测器的自适应模糊控制方法不会产生任何无界信号，系统保持稳定。同时，具有未知偏航率和约束状态的自动驾驶仪航向控制系统可以从给定的设计中受益。