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基于反步控制和神经动力学模型的带缆水下潜器航迹跟踪 被引量:1

Tracking control for tethered underwater vehicle based on backstepping mode and neurodynamics model
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摘要 为实现带缆水下潜器的航迹跟踪控制,对带缆水下潜器设计了运动学反步控制器和动力学滑模控制器,并引入生物启发神经动力学模型来平滑反步控制器中因跟踪误差较大,引起的输出速度跳变。对水下潜器折线路径跟踪进行仿真,并分析脐带缆对跟踪效果的影响。结果显示,所设计控制器的路径跟踪误差小,跟踪速度在初始阶段以及折线路径拐点处过渡平滑;脐带缆使跟踪效果变差。对带缆潜器这一刚性和柔性部件相互连接的水下运载设备而言,神经动力学反步滑模控制器能够较好地实现航迹跟踪,并有效克服传统反步控制器速度跳变的问题。 In order to realize the tracking control of tethered underwater vehicle, this paper designs kinetmatics backstepping controller and dynamics sliding mode controller for tethered underwater vehicle. Bio-inspired neural dynamic model is introduced to smooth the output speed jumping generating by backstepping controller, because of a larger tracking error.Meanwhile the simulation of broken line path tracking is carried out. And the impact on tracking effect by umbilical cable and current and is analyzed. The results indicate that the path tracking error of the designed controller is small, and the tracking speed change is smooth at the initial stage and at the inflection point of the fold line path;the umbilical cable makes the tracking effect worse. For the underwater vehicle with umbilical cable, the neural dynamic back-stepping sliding mode controller is able to achieve tethered underwater vehicle’s trajectory tracking well and overcome the problem of speed jumping of traditional backstepping controller.
作者 魏斯行 刘晗 马宁 李霄霄 WEI Si-hang;LIU Han;MA Ning;LI Xiao-xiao(State Key Laboratory of Ocean Engineering,Shanghai Jiaotong University,Shanghai 200240,China;Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration,Shanghai 200240,China;School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;CETC Ocean Information Co.,Ltd.,Beijing 100041,China)
出处 《舰船科学技术》 北大核心 2020年第1期88-94,共7页 Ship Science and Technology
基金 国家重点基础研究发展计划项目(2014CB046804) 教育部财政部重大科研专项(GKZY010004)
关键词 带缆水下潜器 反步控制 滑模控制 神经动力学 航迹跟踪 tethered underwater vehicle backstepping controller sliding mode controller neurodynamics trajectory tracking
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