吊舱推进无人水面艇的航向保持  

Study on course keeping of POD propulsion unmanned surface vessel

作　　者：慕东东 王国峰[1] 范云生[1] 赵永生[1] 

机构地区：[1]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《哈尔滨工程大学学报》2018年第2期274-281,共8页Journal of Harbin Engineering University

基　　金：国家自然科学基金项目(51609033);辽宁省自然科学基金项目(2015020022);中央高校基本科研业务费专项基金项目(3132014321;3132017133)

摘　　要：针对吊舱推进无人水面艇(unmanned surface vessel,USV)的航向控制问题,本文在建立其响应模型的基础上,根据线性滑模(linear sliding mode,LSM)和非奇异终端滑模(non singular terminal sliding mode,NTSM)在平衡点收敛速度不同的特点,提出了具有较快收敛速度的快速非奇异终端滑模(fast non singular terminal sliding mode,FNTSM)航向保持策略。通过RBF神经网络和扰动观测器分别补偿模型的不确定和外界扰动,同时采用饱和函数和模糊加权来减弱抖振现象以增强系统的鲁棒性。最终将FNTSM与反步自适应航向保持策略进行仿真比较,结果表明:本文提出的FNTSM航向保持策略较传统的自适应控制方法有较快的收敛速度和较强的鲁棒性,证明了本文所述方法的可行性和正确性。Aiming at the course-keeping control of podded propulsion unmanned surface vessel( USV),on the basis of establishing podded propulsion USV response model,and considering that the convergence rate of linear sliding mode( LSM) and non singular terminal sliding mode( NTSM) at equilibrium point is different,a fast non singular terminal sliding mode( FNTSM) course keeping strategy with fast convergence speed was presented. Then RBF neural network was used to approximate the unknown function of the system and disturbance observer was used to compensate disturbance. At the same time,the saturation function and fuzzy weight were used to reduce the chattering caused by the sliding mode control and the control switching,and the robustness of the system was enhanced.FNTSM was compared with backstepping adaptive controller,and the results show that the novel FNTSM course keeping strategy has faster convergence speed and stronger robustness than the traditional backstepping adaptive control method,which proves feasibility and correctness of the proposed method.

关 键 词：无人艇 吊舱 响应模型 航向保持 径向神经网络 扰动观测器 滑模控制 快速收敛 鲁棒性 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]