欠驱动无人艇路径跟踪动态性能约束控制OA
Path tracking based on dynamic performance constraint control for un-manned surface vehicle
为了对欠驱动无人艇路径跟踪艏向角收敛过程中的动态性能约束控制进行研究,本文建立了时变遭遇角下的真实海浪干扰模型代替传统的正余弦叠加的简化模型,引入有限时间干扰观测器和神经网络分别对海浪干扰和模型中的建模误差进行补偿,并通过辅助动态系统解决潜在可能的输入饱和问题;将改进后的障碍李雅普诺夫函数引入控制器的设计之中以此将转艏角速度的收敛速度进行约束;利用李雅普诺夫函数稳定性分析理论证明了系统中的所有误差信号最终都是有界收敛的,并通过SimuNPS数值模拟分析验证了本文控制策略的有效性和可行性.
In this paper,the dynamic performance constraint control in the process of heading angle convergence of path tracking for underactuated USV is studied.Firstly,the real wave disturbance model under time-varying en-counter angle is established to replace the traditional simplified model of sine and cosine superposition.Secondly,the finite-time disturbance observer and neural network are introduced to compensate the wave disturbance and the unknown dynamics in the model respectively,and the potential input saturation problem is solved by the auxiliary dynamic system.Then the improved barrier Lyapunov function is introduced into the design of the controller to con-strain the convergence speed of the yaw rate.Finally,the Lyapunov function stability analysis theory is used to prove that all the error signals in the system are ultimately bounded and convergent,and the effectiveness and feasi-bility of the proposed control strategy are verified by SimuNPS numerical simulation analysis.
慕东东;和瑶;吴韬;范云生;杜国飞
大连海事大学 船舶电气工程学院,辽宁 大连 116026大连海事大学 船舶电气工程学院,辽宁 大连 116026大连海事大学 船舶电气工程学院,辽宁 大连 116026大连海事大学 船舶电气工程学院,辽宁 大连 116026大连海事大学 船舶电气工程学院,辽宁 大连 116026
信息技术与安全科学
欠驱动无人艇路径跟踪动态性能状态约束障碍李雅普诺夫函数反步法神经网络输入饱和
underactuated unmanned surface vehiclepath trackingdynamic performancestate constraintsbar-rier Lyapunov functionbacksteppingneural networkinput saturation
《哈尔滨工程大学学报》 2026 (3)
516-523,8
国家重点研发计划(2022YFB4301401)国家自然科学基金项目(52301360)辽宁省科技厅中试验证项目(2022JH24,10200029)中央高校基本科研业务费专项基金项目(3132024101)中国博士后科学基金项目(2022M710569)辽宁省博士启动基金项目(2022-BS-094)大连市重点科技攻关项目(2023YF11GX007).
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