输入受限下欠驱动AUV轨迹跟踪滑模控制  

Underactuated AUV Trajectory Tracking Sliding Mode Control with Input Limitation

作　　者：李鑫滨[1] 王鹏[1] 骆曦[1] 潘洪涛 LI Xin-bin;WANG Peng;LUO Xi;PANG Hong-tao(Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment,Yanshan University,Qinhuangdao 066004,China)

机构地区：[1]燕山大学智能控制系统与智能装备教育部工程研究中心,河北秦皇岛066004

出　　处：《水下无人系统学报》2022年第1期44-53,共10页Journal of Unmanned Undersea Systems

基　　金：国家自然科学基金项目资助(61873224);河北省省级科技计划项目资助(F2020203037)。

摘　　要：针对欠驱动自主水下航行器(AUV)在外界干扰和输入受限下水平面轨迹跟踪问题,提出了基于非线性干扰观测器和径向基函数(RBF)神经网络的滑模控制器。首先,将欠驱动AUV运动学模型通过坐标变换转换为误差运动学模型镇定位置误差;其次,利用反步法设计艏摇角虚速度控制律,镇定姿态误差;然后采用非线性干扰观测器对时变海流扰动进行估计,并通过滤波器估计虚拟控制律的导数,避免了虚拟控制律求导引起的"微分爆炸";最后,设计自适应RBF神经网络对欠驱动AUV实际输入进行补偿,通过李雅普诺夫稳定性证明闭环跟踪误差所用信号一致有界。仿真验证了所设计控制器的有效性。Aiming at the horizontal plane trajectory tracking problem of the underactuated autonomous undersea vehicle(AUV)under external interferences and limited inputs,a sliding mode controller based on a nonlinear disturbance observer and radial basis function(RBF)neural network was proposed in this study.Firstly,the underactuated AUV kinematics model was transformed into an error kinematics model to stabilize the position error through a coordinate transformation.Secondly,the backward step method was used to design the bow-rocking angle virtual velocity control law to stabilize the attitude error.Subsequently,a nonlinear disturbance observer was used to estimate the disturbance of a time-varying ocean current,and the derivative of the virtual control law was estimated through a filter to avoid the“differential explosion”caused by the derivative of the virtual control law.Finally,an adaptive RBF neural network was designed to compensate the actual input of the underactuated AUV,and the Lyapunov stability proved that the signal used for the closed-loop tracking error was uniformly bounded.The simulation verified the effectiveness of the designed controller.

关 键 词：欠驱动自主水下航行器 输入受限 轨迹跟踪 滑模控制 

分 类 号：TJ630.1[兵器科学与技术—武器系统与运用工程] TB71.2[一般工业技术—真空技术]