• CN:11-2187/TH
  • ISSN:0577-6686

›› 2014, Vol. 50 ›› Issue (19): 50-57.

• 论文 • 上一篇    下一篇

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自主式水下机器人自适应区域跟踪控制

张铭钧;褚振忠   

  1. 哈尔滨工程大学机电工程学院
  • 出版日期:2014-10-05 发布日期:2014-10-05

Adaptive Region Tracking Control for Autonomous Underwater Vehicle

ZHANG Mingjun;CHU Zhenzhong   

  1. College of Mechanical Electrical Engineering, Harbin Engineering University
  • Online:2014-10-05 Published:2014-10-05

摘要: 研究自主式水下机器人的区域跟踪控制问题,提出一种基于PD神经滑模的自适应区域跟踪控制方法。针对自主式水下机器人自适应控制器中仅在线调整网络权值的径向基函数神经网络存在收敛性能差的问题,给出同时对径向基函数神经网络权值、径向基函数中心与方差进行自适应调整的方法,使径向基函数神经网络无须离线选取径向基函数中心与方差,即可进行在线自适应学习。考虑到控制器中滑模控制项易引起系统抖振的问题,提出一种基于指数函数的滑模切换增益调节方法,使滑模切换增益能够依据跟踪误差实时调节以降低系统抖振。基于Lyapunov理论对所提自适应区域跟踪控制方法的稳定性进行分析。通过自主式水下机器人的仿真试验与水池试验验证所提方法的有效性。

关键词: 水下机器人;区域跟踪控制;滑模控制;神经网络控制

Abstract: The problem of region tracking control method for autonomous underwater vehicle is researched, and an adaptive region tracking control method based on PD-neural-sliding mode is proposed. Aiming at the problem of weak convergence capability of the radial basis function neural networks which only adjust the networks weights on line in the autonomous underwater vehicle adaptive controller, the simultaneous adaptive adjustment method for radial basis function neural networks weights, radial basis function centers and variance is given. The method makes radial basis function neural networks do not need to select radial basis function centers and variance offline, and online adaptive learning can be achieved. Considering that the system chattering problem which is easily caused by sliding mode item, a switch gain adjust method based on exponential function is proposed, which enables sliding mode switch gain real-time adjustment according to tracking error in order to reduce system chattering. The stability analysis of the proposed adaptive region tracking control method is carried out based on Lyapunov theory. The simulation experimental and pool experimental based on autonomous underwater vehicle are presented to demonstrate the effectiveness of the proposed method.

Key words: underwater vehicle;region tracking control;sliding mode control;neural networks control

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