Neural network-based adaptive robust control for a class of uncertain systems with measurement noise

Jinyong Yang; Yingmin Jia

Neural network-based adaptive robust control for a class of uncertain systems with measurement noise

Jinyong Yang^*
, Yingmin Jia

^*此作品的通讯作者

自动化科学与电气工程学院

Beihang University

科研成果: 会议稿件 › 论文 › 同行评审

2 引用（Scopus）

摘要

In this paper, neural networks (NNs) and adaptive robust control (ARC) design philosophy are integrated to design performance-oriented control laws for a class of uncertain systems whose output is corrupted by external disturbances. The derived adaptive-robust control schemes not only guarantee all the signals are bounded in the closed loop but also make the system preserve certain prescribed properties. The cone-bounded assumption on the uncertain dynamics is removed via neural networks. The feedback information is the state with measurement noise.

源语言	英语
页	1475-1478
页数	4
出版状态	已出版 - 2002
活动	2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering - Beijing, 中国期限: 28 10月 2002 → 31 10月 2002

会议

会议	2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
国家/地区	中国
市	Beijing
时期	28/10/02 → 31/10/02

其它文件与链接

链接到 Scopus 的出版物

引用此

@conference{cc8e7aea09a545978bd68061db8d2a03,

title = "Neural network-based adaptive robust control for a class of uncertain systems with measurement noise",

abstract = "In this paper, neural networks (NNs) and adaptive robust control (ARC) design philosophy are integrated to design performance-oriented control laws for a class of uncertain systems whose output is corrupted by external disturbances. The derived adaptive-robust control schemes not only guarantee all the signals are bounded in the closed loop but also make the system preserve certain prescribed properties. The cone-bounded assumption on the uncertain dynamics is removed via neural networks. The feedback information is the state with measurement noise.",

keywords = "Measurment noise, Neural networks, Robust adaptive control, Uncertain systems",

author = "Jinyong Yang and Yingmin Jia",

year = "2002",

language = "英语",

pages = "1475--1478",

note = "2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering ; Conference date: 28-10-2002 Through 31-10-2002",

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TY - CONF

T1 - Neural network-based adaptive robust control for a class of uncertain systems with measurement noise

AU - Yang, Jinyong

AU - Jia, Yingmin

PY - 2002

Y1 - 2002

N2 - In this paper, neural networks (NNs) and adaptive robust control (ARC) design philosophy are integrated to design performance-oriented control laws for a class of uncertain systems whose output is corrupted by external disturbances. The derived adaptive-robust control schemes not only guarantee all the signals are bounded in the closed loop but also make the system preserve certain prescribed properties. The cone-bounded assumption on the uncertain dynamics is removed via neural networks. The feedback information is the state with measurement noise.

AB - In this paper, neural networks (NNs) and adaptive robust control (ARC) design philosophy are integrated to design performance-oriented control laws for a class of uncertain systems whose output is corrupted by external disturbances. The derived adaptive-robust control schemes not only guarantee all the signals are bounded in the closed loop but also make the system preserve certain prescribed properties. The cone-bounded assumption on the uncertain dynamics is removed via neural networks. The feedback information is the state with measurement noise.

KW - Measurment noise

KW - Neural networks

KW - Robust adaptive control

KW - Uncertain systems

UR - https://www.scopus.com/pages/publications/0037661137

M3 - 论文

AN - SCOPUS:0037661137

SP - 1475

EP - 1478

T2 - 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering

Y2 - 28 October 2002 through 31 October 2002

ER -

Neural network-based adaptive robust control for a class of uncertain systems with measurement noise

摘要

会议

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指纹

引用此