摘要
研究了一个3自由度(DOF)无人水面舰艇的轨迹追踪控制问题,具有不确定性的动力学模型和不可预测的外部扰动使其数学模型很难被精确获得。提出了利用径向基函数神经网络的设计,通过反推的方式,设计了一个稳定的自适应神经网络控制器,达到设定轨迹控制和所有信号有界的目标。通过李雅普诺夫稳定定律证明了该未知系统的稳定性。仿真结果证实了该控制的有效性。
The trajectory tracking control for an uncertain 3-DOF unmanned surface vessels is studied in this paper.Due to the uncertainty of its dynamic model and inscrutabilily of the external disturbance,it is hard to obtain its accurate mathematical model.An adaptive radial basis function neural network is proposed,which is used to design the system.Via the method of backstepping,a stable adaptive NN controller is designed to achieve the proscribed tracking performances and ensure the boundedness of all the signals.Subsequently,the stability of the unknown system is guaranteed via Lyaponov’s stability theory.The simulation results are used to demonstrate the effectiveness of the proposed control.
作者
夏俊
XIA Jun(School of Electric Power,South China University of Technology,Guangzhou 510640,China)
出处
《机械制造与自动化》
2019年第3期185-188,共4页
Machine Building & Automation
关键词
自适应神经网络控制
径向基函数
无人水面舰艇
设定规矩追踪
障碍李雅普诺夫
adaptive neural network control
radial basis function
unmanned surface vessels
prescribed trajectory tracking
Barrier Lyapunov function
