自主水下航行器事件触发自适应神经渐近轨迹跟踪控制  

Event-triggered adaptive neural asymptotic trajectory tracking control of autonomous underwater vehicles

作　　者：唐思星 邓英杰 赵运利 TANG Sixing;DENG Yingjie;ZHAO Yunli(School of Mechanical Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China)

机构地区：[1]燕山大学机械工程学院,河北秦皇岛066004

出　　处：《燕山大学学报》2025年第2期114-120,共7页Journal of Yanshan University

基　　金：国家自然科学基金青年基金资助项目(52101375);河北省自然科学基金资助项目(E2021203142)。

摘　　要：针对六自由度自主水下航行器在水平面的高精度轨迹跟踪问题,提出了一种事件触发自适应神经渐近跟踪控制的方法。采用径向基神经网络对未知模型和环境干扰等非线性不确定项进行逼近,将积分有界函数融入控制律和自适应律中,以实现跟踪误差的渐进收敛;通过最小学习参数技术压缩神经网络权值,构造出单参数的自适应律;在控制器至执行器通道上应用事件触发机制,构造变量式事件触发条件,避免了Zeno现象的发生;通过Lyapunov直接法和Barabalat引理对闭环系统的渐近稳定性进行分析。最后,通过仿真试验验证所提出控制策略的优越性和平稳性。Aiming at the high-precision trajectory tracking control of autonomous underwater vehicles on the horizontal plane,an event-triggered adaptive neural asymptotic tracking control scheme is developed.The radial basis function neural networks approximate the uncertain terms composed of environmental disturbances,unknown model dynamics and the derivatives of virtual control laws,and the minimum learning parameter technique is adopted to construct the nonlinear damping terms in the control laws and the single-parameter adaptive laws.The integral-bounded functions are incorporated in the control design.The triggering conditions with the variable thresholds are designed in the controller-to-actuator channel.The separate event-triggered asymptotic controllers are derived.Through the Lyapunov's direct method and the Barbalat's lemma,the asymptotic stability of the closed-loop system is proved.Finally,the superiority of the proposed scheme is verified through the simulation.

关 键 词：自主水下航行器 渐近跟踪控制 最小学习参数 事件触发控制 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]