摘要
针对欠驱动无人艇在路径跟踪过程中海流的时变干扰、传感器噪声污染及控制器参数不易整定等问题,设计路径跟踪控制器。引入视线法获取艏向角,作为控制器的控制目标,并利用卡尔曼滤波器对数据融合处理;改进扩张状态观测器的非线性函数为自适应galn函数,抑制噪声,提高观测精度;利用灰狼优化算法优化目标函数,获取最优控制器参数,提升了控制效率;通过仿真和湖泊试验,验证了所设计控制器能够实现对无人艇的高效控制,路径跟踪精度整体提升。
Aiming to solve the problems of time-varying interference of ocean current,sensor noise pollution and controller parameters difficult to be set during the path tracking of underdriven unmanned surface vehicle,a path tracking controller is designed.The line-of-sight method is introduced to obtain the heading angle as the control target of the controller,and the Kalman filter is used for fusing the data.The nonlinear function of the extended state observer is improved and regarded as an adaptive galn function,which can suppress the noise and improve the observation accuracy.The grey wolf optimization algorithm is used for optimizing the objective function,obtaining the optimal controller parameters and improving the control efficiency.Through simulation and lake tests,it is verified that the designed controller can achieve the efficient control of unmanned vehicle,and improve the tracking accuracy of the overall path.
作者
赵源
戴晓强
王莹
曾庆军
李昂
李维
Zhao Yuan;Dai Xiaoqiang;Wang Ying;Zeng Qingjun;Li Ang;Li Wei(School of Automation,Jiangsu University of Science and Technology,Zhenjiang 212100,China;School of Computing Science,Jiangsu University of Science and Technology,Zhenjiang 212100,China)
出处
《战术导弹技术》
北大核心
2023年第4期95-102,118,共9页
Tactical Missile Technology
基金
江苏省科技项目(BE2018103)。
关键词
欠驱动
路径跟踪
自适应galn函数
自抗扰控制
灰狼优化
目标函数
视线法
underdrive
path tracking
adaptive galn function
active disturbance rejection control
gray wolf optimization
objective function
line-of-sight method
