文献类型：期刊文献

英文题名：Robust fixed-time H∞ tracking control of UUVs with partial and full state constraints and prescribed performance under input saturation

作者：Liu, Haitao[1,2]; Qi, Zhenghong[1]; Yuan, Jianbin[1]; Tian, Xuehong[1,2]

机构：[1] School of Mechanical Engineering, Guangdong Ocean University, Zhanjiang, 524088, China; [2] Shenzhen Institute of Guangdong Ocean University, Shenzhen, 518120, China

年份：2023

卷号：283

外文期刊名：Ocean Engineering

收录：EI(收录号：20232514276800)

语种：英文

外文关键词：Backstepping - Closed loop control systems - Lyapunov functions - Navigation - Radial basis function networks - Time varying control systems - Unmanned underwater vehicles - Vehicle performance

外文摘要：In this paper, a fixed-time tracking control problem for an unmanned underwater vehicle (UUV) is investigated in the case of strong external sudden disturbances, model uncertainty, time-varying disturbances and specified performance constraints. First, a modified barrier Lyapunov function (QABLF) is proposed to increase applicability by introducing the standard quadratic Lyapunov function (QLF) and the logarithmic asymmetric barrier Lyapunov function (ABLF). The QALBF has two types and can be constructed to avoid violations of full and partial state constraints by parameter modification. Second, adaptive antisaturation appointed-time prescribed performance functions (APPFs) are introduced in the QABLF for the first time to relax the overshoot restriction and reduce the effect of input saturation on the performance constraint. Third, based on the backstepping method, a robust H∞ control strategy is developed to address strong, sudden disturbances. An auxiliary variable is designed to compensate for input saturation. Next, an improved adaptive radial basis function neural network (ARBFNN) is proposed to match the time-varying disturbances and model uncertainty. Finally, composite robust fixed-time control is achieved with high robustness and transient performance, which guarantees that the closed-loop system is fixed-time convergent. Moreover, the feasibility of the proposed controller is verified by Lyapunov analysis and numerical simulation. ? 2023 Elsevier Ltd