中国物理B ›› 2012, Vol. 21 ›› Issue (3): 30502-030502.doi: 10.1088/1674-1056/21/3/030502

• GENERAL • 上一篇    下一篇

Mohammad Pourmahmood Aghababa   

  • 收稿日期:2011-07-23 修回日期:2011-08-17 出版日期:2012-02-15 发布日期:2012-02-15
  • 通讯作者: Mohammad Pourmahmood Aghababa,m.p.aghababa@ee.uut.ac.ir; m.pour13@gmail.com E-mail:m.p.aghababa@ee.uut.ac.ir; m.pour13@gmail.com

Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems

Mohammad Pourmahmood Aghababa   

  1. Electrical Engineering Department, Urmia University of Technology, Urmia, Iran
  • Received:2011-07-23 Revised:2011-08-17 Online:2012-02-15 Published:2012-02-15
  • Contact: Mohammad Pourmahmood Aghababa,m.p.aghababa@ee.uut.ac.ir; m.pour13@gmail.com E-mail:m.p.aghababa@ee.uut.ac.ir; m.pour13@gmail.com

Abstract: The centrifugal flywheel governor (CFG) is a mechanical device that automatically controls the speed of an engine and avoids the damage caused by sudden change of load torque. It has been shown that this system exhibits very rich and complex dynamics such as chaos. This paper investigates the problem of robust finite-time synchronization of non-autonomous chaotic CFGs. The effects of unknown parameters, model uncertainties and external disturbances are fully taken into account. First, it is assumed that the parameters of both master and slave CFGs have the same value and a suitable adaptive finite-time controller is designed. Second, two CFGs are synchronized with the parameters of different values via a robust adaptive finite-time control approach. Finally, some numerical simulations are used to demonstrate the effectiveness and robustness of the proposed finite-time controllers.

Key words: finite-time controller, chaos synchronization, non-autonomous centrifugal flywheel governor, chaotic system

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a
05.45.Xt (Synchronization; coupled oscillators) 05.45.Gg (Control of chaos, applications of chaos) 05.45.Pq (Numerical simulations of chaotic systems)