Neuro-adaptive containment control of unmanned surface vehicles with disturbance observer and collision-free. (October 2022) - Deng, Qun; Peng, Yan; Qu, Dong; Han, Tao; Zhan, Xisheng
Abstract: The adaptive containment control problem with collision avoidance is investigated for unmanned surface vehicles (USVs). At first, the finite time disturbance observer is developed to present the estimation and compensation of external disturbance. Then, incorporating the artificial potential and radial basis function into the new containment strategy, all followers can enter the convex hull spanned by leaders while the collision is avoided. Furthermore, it is demonstrated that the error signals in the closed-loop system are boundedness by employing Lyapunov stability. Simulation studies finally manifest the effectiveness of proposed method. Highlights: The paper achieves the containment control of unmanned surface vehicles with collision avoidance. To approximate the model uncertainties, the containment control law with neural network is developed. The finite-time disturbance observer provides an estimation and compensation of the disturbance.