Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network

Yanqiu Che, Ting Ting Yang, Xiao Qin Li, Rui Xue Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.

Original languageEnglish (US)
Title of host publicationMechanical Engineering, Industrial Electronics and Information Technology Applications in Industry
Pages1101-1104
Number of pages4
DOIs
StatePublished - Oct 30 2013
Event2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013 - Chongqing, China
Duration: Sep 14 2013Sep 15 2013

Publication series

NameApplied Mechanics and Materials
Volume427-429
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013
CountryChina
CityChongqing
Period9/14/139/15/13

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network'. Together they form a unique fingerprint.

Cite this