为满足欠驱动自主水下航行器(autonomous underwater vehicle，AUV)在复杂扰动和参数不确定条件下高性能轨迹跟踪需求，提出预设动态性能及收敛时间的三维轨迹跟踪控制方法。首先，对欠驱动AUV的前向位置道进行扩维，构建面向控制的一体化多输入多输出轨迹跟踪模型。然后，结合动态过程函数与预设时间控制理论，建立动态性能预设轨迹跟踪控制系统，使得AUV轨迹跟踪暂态品质可由动态过程函数直接决定，而跟踪误差的实际收敛时间也可由单个控制参数准确预设。最后，为避免控制奇异现象和"微分爆炸"现象，控制系统设计过程中分别融入绝对值修正法和径向基函数网络(radial basis function neural network，RBFNN)拟合法。数值仿真结果表明，所提出的控制方法可显著提升欠驱动AUV的抗扰性和暂态品质，实现快速平滑的高性能三维轨迹跟踪。
Trajectory tracking control with predefined dynamic performance for underactuated autonomous underwater vehicle
To meet the high-performance trajectory tracking requirements of underactuated autonomous underwater vehicle(AUV)under complex disturbances and parameter uncertainty,a three-dimensional trajectory tracking controller method with predefined dynamic performance and convergence time is proposed.Firstly,by extending the forward position channel of the underactuated AUV,and a multi-input multi-output trajectory tracking control-oriented model is developed.Subsequently,by combining dynamic process functions with predefined-time control theory,a dynamic performance-predefined trajectory tracking control system is established,which allows the transient quality of AUV trajectory tracking to be determined by dynamic process functions,and the actual convergence time of tracking errors to be predefined by a single control parameter.Finally,to avoid control singularities and the"differential explosion"phenomenon,the controller design incorporates the absolute value correction method and radial basis function neural network(RBFNN)fitting method.Numerical simulation results indicate that the proposed controller significantly improves the disturbance rejection and transient quality of underactuated AUV,achieving fast,smooth,and high-performance trajectory tracking.
autonomous underwater vehicle(AUV)dynamic process functionpredefined-time control theorydynamic performance-predefined trajectory tracking controlradial basis function neural network(RBFNN)
万方数据
维普
