船舶航向非线性系统鲁棒跟踪控制

Robust tracking control of nonlinear ship steering

中文关键词  船舶航向跟踪控制  非匹配不确定性  神经网络  L2增益设计  Lyapunov函数递归设计

英文关键词  ship tracking control  unmatched uncertainties  neural networks  L-two-gain design  Lyapunov function recursive design

中文摘要

      对船舶航向非线性系统, 提出了一种基于神经网络方法的鲁棒跟踪控制器. 系统由船舶运动非线性响应模型和舵机伺服系统串联构成, 其中运动响应模型考虑了建模误差和外界干扰力等非匹配不确定性. 对建模误差和期望舵角的一阶导数项应用在线二层神经网络予以辨识和补偿, 不确定性干扰项处理应用L2增益设计. 采用Lyapunov函数递推法, 得到包括神经网络权值算法在内的跟踪控制器. 跟踪误差和神经网络权值误差的一致终值有界性保证了系统的鲁棒稳定性, 合理的控制器参数选择保证了控制精度. 仿真结果验证了控制器的有效性.

英文摘要

      A robust neural network based autopilot is proposed for ship steering control of surface ships with unmatched uncertainties. The cascaded system consists of the nonlinear ship response model and the rudder actuator dynamics. The response model takes account of the modeling errors and external disturbances. The modeling errors and the derivative of desired rudder are identified and subsequently compensated by two online two-layer neural networks, while the uncertain disturbances are suppressed by using L-two-gain design. By using the method of recursive Lyapunov functions, a robust tracking controller and tuning algorithms of weights are obtained. The uniformly ultimate boundedness of the tracking errors and weight errors guarantees the robust stability of the controller, while the appropriate selection of parameters in the controller guarantees the tracking precision. The results of simulation demonstrate the validity of the presented controller.