基于RBF积分滑模的无人艇集群协同路径跟踪控制

Collaborative Path Tracking Control Method of USV Cluster Based on RBF Integral Sliding Mode

为满足船舶护航、目标围捕等任务要求,文中提出了一种基于路径参数循环的欠驱动无人艇集群协同路径跟踪控制方法。在运动学设计方面,结合视线制导与一致性算法,设计无人艇集群协同制导律,得到闭曲线上对称的编队队形,实现对目标点进行围捕。在动力学设计方面,考虑动力学模型不确定性及传统滑模导致的抖振问题,利用神经网络逼近特性和饱和函数,设计基于自适应径向基函数神经网络的分布式积分滑模控制器,保证无人艇能够精确跟踪制导信号,从而提高系统抗干扰性和路径跟踪精度。Lyapunov稳定性分析证明了闭环系统误差是全局渐近稳定的。仿真结果表明了所提出集群协同控制方法的有效性。

To meet the requirements of ship escorts and target enclosure,a collaborative path tracking control method for underactuated unmanned surface vessel(USV)cluster based on a path parameter cycle is proposed in this study.In a kinematics design that includes line-of-sight guidance and a consistency algorithm,a collaborative guidance law is designed for the USV cluster.This design realizes symmetrical formation on a closed curve and target enclosure.In a dynamics design in which model uncertainties and chattering induced by the traditional sliding mode are considered,a distributed integral sliding mode controller based on an adaptive radial basis function neural network is designed.This distributed integral sliding mode controller uses the approximation characteristics of the neural network and the saturation function to ensure that the USV can track guidance signals accurately,thereby improving the anti-interference of the system and path tracking accuracy.The study also conducts a Lyapunov stability analysis to show that the errors of the closed-loop system are globally asymptotically stable.Simulation results reveal the effectiveness of the proposed collaborative path tracking control method.