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山东大学学报 (工学版) ›› 2019, Vol. 49 ›› Issue (3): 47-56.doi: 10.6040/j.issn.1672-3961.0.2018.385

• 控制科学与工程 • 上一篇    下一篇

考虑未知死区非线性的自适应模糊神经UUV航迹跟踪控制

马川1,2(),刘彦呈1,*(),刘厶源1,张勤进1   

  1. 1. 大连海事大学轮机工程学院, 辽宁 大连 116026
    2. 青岛远洋船员职业学院轮机系, 山东 青岛 266071
  • 收稿日期:2018-09-10 出版日期:2019-06-20 发布日期:2019-06-27
  • 通讯作者: 刘彦呈 E-mail:machuan1984@126.com;liuyc@dlmu.edu.cn
  • 作者简介:马川(1984—)，男，山东青岛人，讲师，博士研究生，主要研究方向为船舶及无人水下航行器智能控制. E-mail: machuan1984@126.com
  • 基金资助:
    国家自然科学基金项目(51479018);中央高校基本科研业务费专项资金资助(3132016335)

Robust adaptive self-organizing neuro-fuzzy tracking control of UUV with unknown dead-zone nonlinearity

Chuan MA1,2(),Yancheng LIU1,*(),Siyuan LIU1,Qinjin ZHANG1   

  1. 1. College of Marine Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China
    2. Department of Marine Engineering, Qingdao Ocean Shipping Mariners College, Qingdao 266071, Shandong, China
  • Received:2018-09-10 Online:2019-06-20 Published:2019-06-27
  • Contact: Yancheng LIU E-mail:machuan1984@126.com;liuyc@dlmu.edu.cn
  • Supported by:
    国家自然科学基金项目(51479018);中央高校基本科研业务费专项资金资助(3132016335)

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摘要：

针对无人水下航行器(unmanned underwater vehicles, UUV)在航迹跟踪控制中存在未知死区非线性和工作环境不确定性的问题,提出一种鲁棒自适应自组织模糊神经控制策略,采用滑模趋近律控制框架和自组织模糊神经网络逼近器在线估计系统未知状态和进行参数的自适应,并采用有限增益鲁棒控制器补偿重构误差。根据李雅普诺夫稳定性理论分析证明所有参数和跟踪状态均有界,并且当时间趋向于无穷大时,跟踪误差及其导数都趋向于零且闭环系统的信号有界。通过与已有控制策略对比仿真表明,该控制策略具有先进性和有效性,对无人水下航行器设计具有指导意义。

关键词: 无人水下航行器, 鲁棒自适应控制, 自组织模糊神经网络, 滑模趋近律控制, 未知死区非线性, 航迹跟踪

Abstract:

A robust adaptive self-organizing neuro-fuzzy control scheme for trajectory tracking of unmanned underwater vehicle with uncertainties and unknown dead-zone nonlinearity was proposed. The scheme adopted a novel sliding mode reaching law control framework and a self-organizing neuro-fuzzy network approximator to estimate the unknown dynamic and self-adaptive the parameter. The robust controller was employed to provide the finite L2-gain property to cope with reconstruction errors. Lyapunov stability theory analysis showed that tracking errors and their derivatives were stable and all signals in the closed-loop system were bounded. Comparative simulation results demonstrated the effectiveness and superiority of the proposed scheme, which could be a reference for the design of unmanned underwater vehicle.

Key words: UUV, robust adaptive tracking control, self-organizing neuro-fuzzy network, sliding mode reaching law control, unknown dead-zone nonlinearity, trajectory tracking

中图分类号: 

  • U665.2

图1

无人水下航行器的推进器分布情况"

图2

RASNFC控制策略的结构图"

图3

UUV参考航迹和实际航迹的对比图"

图4

UUV参考和实际航迹的姿态对比图"

图5

UUV参考和实际航迹的姿态导数的对比图"

图6

不同控制策略的跟踪误差e比较图"

图7

不同控制策略的跟踪误差导数${\mathit{\boldsymbol{\dot e}}}$比较图"

表1

不同控制策略的性能比较"

控制策略瞬态稳态性能运算时间/mse1e2e3e4e5${{\dot e}_1}$${{\dot e}_2}$${{\dot e}_3}$${{\dot e}_4}$${{\dot e}_5}$
AFSMC一般1.3546538216139651991712
FNNISMC一般1.1219429913124742671613
DSNFN较好1.0741334208067850491512
RASNFC很好0.7301050202020741051211
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