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Robust adaptive steering control for unmanned surface vehicle with unknown control direction and input saturation

机译:控制方向和输入饱和度未知的无人水面车辆的鲁棒自适应转向控制

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摘要

A robust adaptive steering control method is proposed to solve the control problem of the unmanned surface vehicle (USV) with uncertainties, unknown control direction, and input saturation. In the controller design process, the adaptive fuzzy system is incorporated into dynamic surface control (DSC) to approximate the uncertainty term induced by external environmental disturbances and model parameters. Then, the Nussbaum function is used to eliminate the requirement for a priori knowledge of the control direction. Besides, to handle the input saturation, the adaptive fuzzy DSC is extended by a second-order nonlinear filter and antisaturation auxiliary function to compensate for the magnitude and rate saturation of the rudder. All signals of the closed-loop system are proven to be uniformly ultimately bounded (UUB) by Lyapunov theorem and the Lemma of Nussbaum gain, and the course error can converge to a small neighborhood of zero through choosing design parameters appropriately. Finally, simulation results and comprehensive comparisons are shown for the USV course system, which is demonstrative of the proposed controller's effectiveness and robustness.
机译:提出了一种鲁棒的自适应转向控制方法,以解决具有不确定性,未知控制方向和输入饱和度的无人机的控制问题。在控制器设计过程中,将自适应模糊系统并入动态表面控制(DSC)中,以近似估算由外部环境干扰和模型参数引起的不确定性项。然后,使用Nussbaum函数消除了对控制方向的先验知识的需求。此外,为处理输入饱和度,自适应模糊DSC由二阶非线性滤波器和抗饱和辅助功能扩展,以补偿方向舵的幅度和速率饱和度。 Lyapunov定理和Nussbaum增益的Lemma证明了闭环系统的所有信号都是一致的最终有界(UUB),并且通过适当选择设计参数,航向误差可以收敛到零附近。最后,给出了USV课程系统的仿真结果和综合比较结果,证明了所提出控制器的有效性和鲁棒性。

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