In this paper, the design problem of intelligent ship autopilot with unmeasured yaw rate and input saturation is investigated based on adaptive fuzzy control. First, an adaptive fuzzy output feedback controller is proposed, then, to improve the convergence speed of the tracking error in the sense of finite time, a finite-time adaptive fuzzy output feedback controller is also designed to improve the control performance. By employing fuzzy logic system (FLS) to estimate the unknown nonlinear function, an adaptive fuzzy state observer is designed to estimate the unmeasured state. An adaptation auxiliary signal for input saturation is also established to compensate the mismatch between the controller signal and the actuator signal. Combining state observer model with backstepping method, two different adaptive fuzzy output-feedback controllers with composite parameter adaptive laws are constructed, respectively. Based on Lyapunov theory, it is proved that all signals in the closed-loop systems are bounded. Finally, the simulation results are conducted to demonstrate the effectiveness of the proposed schemes.

中文翻译：

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基于观测器的输入饱和智能船舶自动驾驶自适应模糊控制

本文研究了基于自适应模糊控制的偏航角和输入饱和度无法测量的智能船舶自动驾驶仪的设计问题。首先，提出了一种自适应模糊输出反馈控制器，然后，为了提高有限时间意义上跟踪误差的收敛速度，还设计了一种有限时间自适应模糊输出反馈控制器，以提高控制性能。通过使用模糊逻辑系统（FLS）估计未知的非线性函数，设计了一种自适应模糊状态观测器来估计未测量状态。还建立了用于输入饱和的自适应辅助信号，以补偿控制器信号和执行器信号之间的不匹配。将状态观测器模型与反推方法相结合，分别构造了两种具有复合参数自适应律的自适应模糊输出反馈控制器。基于李雅普诺夫理论，证明了闭环系统中的所有信号都是有界的。最后，通过仿真结果证明了所提方案的有效性。