基于DSC的鲁棒自适应神经网络航向控制器设计

H. Sun, Fengwei Yu, Jinlu Sheng
{"title":"基于DSC的鲁棒自适应神经网络航向控制器设计","authors":"H. Sun, Fengwei Yu, Jinlu Sheng","doi":"10.12696/GSAM.2013.1015","DOIUrl":null,"url":null,"abstract":"This paper describes an adaptive course controller with rudder dynamics. The model is described by a third order nonlinear model with unknown parameters. An adaptive neural network (NN )control algorithm based on dynamic surface control (DSC) is developed. With only one learning parameter and reduced computation load, the proposed algorithm can avoid both problem of “explosion of complexity” in the conventional backstepping method and singularity problem. In addition, the boundedness stability of the closed-loop system is guaranteed and tracking error can be made arbitrary small. The effectiveness of the presented autopilot has been demonstrated in the simulation.","PeriodicalId":177039,"journal":{"name":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust adaptive NN course controller design based on DSC\",\"authors\":\"H. Sun, Fengwei Yu, Jinlu Sheng\",\"doi\":\"10.12696/GSAM.2013.1015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an adaptive course controller with rudder dynamics. The model is described by a third order nonlinear model with unknown parameters. An adaptive neural network (NN )control algorithm based on dynamic surface control (DSC) is developed. With only one learning parameter and reduced computation load, the proposed algorithm can avoid both problem of “explosion of complexity” in the conventional backstepping method and singularity problem. In addition, the boundedness stability of the closed-loop system is guaranteed and tracking error can be made arbitrary small. The effectiveness of the presented autopilot has been demonstrated in the simulation.\",\"PeriodicalId\":177039,\"journal\":{\"name\":\"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12696/GSAM.2013.1015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12696/GSAM.2013.1015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了一种带有方向舵动力学的自适应航向控制器。该模型用一个带未知参数的三阶非线性模型来描述。提出了一种基于动态面控制(DSC)的自适应神经网络控制算法。该算法只需要一个学习参数,减少了计算量,既避免了传统反演方法的“复杂度爆炸”问题,又避免了奇异性问题。同时保证了闭环系统的有界稳定性,使得跟踪误差可以任意小。仿真结果验证了该自动驾驶仪的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Robust adaptive NN course controller design based on DSC
This paper describes an adaptive course controller with rudder dynamics. The model is described by a third order nonlinear model with unknown parameters. An adaptive neural network (NN )control algorithm based on dynamic surface control (DSC) is developed. With only one learning parameter and reduced computation load, the proposed algorithm can avoid both problem of “explosion of complexity” in the conventional backstepping method and singularity problem. In addition, the boundedness stability of the closed-loop system is guaranteed and tracking error can be made arbitrary small. The effectiveness of the presented autopilot has been demonstrated in the simulation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A dynamic scheduling parallel test system with CVI A research of algorithm based on probability weighted fuzzy association rules Design of assembly line of diesel engine factory based on RFID technology Application of genetic algorithm in computer aided design A new method of parameters determined in image recognition by PCNN
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1