自适应量化神经网络滑模无人船编队控制  

Adaptive quantization neural network sliding mode control for unmanned ship formation

作　　者：宁君[1] 刘子涵 李伟[1] 李铁山 陈俊龙 NING Jun;LIU Zihan;LI Wei;LI Tieshan;CHEN Junlong(Navigation College,Dalian Maritime University,Dalian 116026,Liaoning,China;College of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611730,Sichuan,China;College of Computer Science and Engineering,South China University of Technology,Guangzhou 510641,Guangdong,China)

机构地区：[1]大连海事大学航海学院,辽宁大连116026 [2]电子科技大学自动化工程学院,四川成都611730 [3]华南理工大学计算机科学与工程学院,广东广州510641

出　　处：《上海海事大学学报》2024年第2期7-13,共7页Journal of Shanghai Maritime University

基　　金：国家自然科学基金(51939001,61976033,61803064);中央高校基本科研业务费(3132023135);辽宁省自然科学基金(20170540098)。

摘　　要：针对复杂海洋环境下欠驱动水面无人船(unmanned surface vehicle,USV)编队控制存在的模型不确定性、参数摄动、控制输入量化等问题,提出一种自适应量化神经网络滑模控制算法。在USV运动学子系统中,设计基于内外环控制策略的制导律,解决USV欠驱动问题。由于所采用的动力学模型中含有未知项和外界环境干扰,故在USV动力学子系统中通过使用径向基函数神经网络实现对干扰的估计。采用一种线性解析模型来描述输入量化过程。所设计的控制系统不需要量化参数的先验信息。基于输入-状态稳定性理论证明了系统稳定性。通过仿真实验验证了所提算法的有效性。Aiming at the model uncertainty,parameter perturbation and control input quantification problems in the formation control of underactuated unmanned surface vehicles(USVs) under complex marine environment,a sliding mode control algorithm of adaptive quantification neural network is proposed.In the USV dynamic subsystem,the guidance law based on the inner and outer loop control strategy is designed to solve the USV underactuated problem.Because the adopted dynamic model contains unknown terms and external environment interference,the radial basis function neural network is used to realize the estimation of interference in the USV dynamic subsystem.A linear analytical model is used to describe the input quantification process.The designed control system does not need the prior information of quantitative parameters.The system stability is proved based on the input-to-state stability theory.The effectiveness of the proposed algorithm is verified by the simulation experiment.

关 键 词：自适应滑模控制 输入量化 编队控制 水面无人船(USV) 

分 类 号：U664.82[交通运输工程—船舶及航道工程]