Neural network-based sliding mode control for a class of uncertain systems with measurement noise

Jinyong Yang; Yingmin Jia

Neural network-based sliding mode control for a class of uncertain systems with measurement noise

Jinyong Yang^*
, Yingmin Jia

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Beihang University

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.

Original language	English
Pages	1479-1482
Number of pages	4
State	Published - 2002
Event	2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering - Beijing, China Duration: 28 Oct 2002 → 31 Oct 2002

Conference

Conference	2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Country/Territory	China
City	Beijing
Period	28/10/02 → 31/10/02

Keywords

Measurement noise
Neural networks
Nonlinear systems
Sliding mode control

Cite this

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

abstract = "In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.",

keywords = "Measurement noise, Neural networks, Nonlinear systems, Sliding mode control",

author = "Jinyong Yang and Yingmin Jia",

year = "2002",

language = "英语",

pages = "1479--1482",

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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T1 - Neural network-based sliding mode control for a class of uncertain systems with measurement noise

AU - Yang, Jinyong

AU - Jia, Yingmin

PY - 2002

Y1 - 2002

N2 - In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.

AB - In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.

KW - Measurement noise

KW - Neural networks

KW - Nonlinear systems

KW - Sliding mode control

UR - https://www.scopus.com/pages/publications/0037661136

M3 - 论文

AN - SCOPUS:0037661136

SP - 1479

EP - 1482

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 sliding mode control for a class of uncertain systems with measurement noise

Abstract

Conference

Keywords

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Cite this