Modified dynamic minimization algorithm for parameter estimation of chaotic system from a time series

This paper proposes a modified dynamic minimization algorithm for parameter estimation of chaotic systems, based on a scalar time series. Comparing with the previous design proposed by Maybhate and Amritkar (Phys. Rev. E 59:284–293, 1999 ), two important new design concepts related to the feedback c...

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Vydané v:Nonlinear dynamics Ročník 66; číslo 1-2; s. 213 - 229
Hlavní autori: Liu, Ying, Tang, Wallace K. S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 01.10.2011
Springer Nature B.V
Predmet:
Algorithms
Automotive Engineering
Chaos theory
Circuits
Classical Mechanics
Computer simulation
Control
Design engineering
Dynamical Systems
Engineering
Feedback control
Mathematical models
Mechanical Engineering
Minimization
Nonlinear dynamics
Optimization
Original Paper
Parameter estimation
Parameter modification
Robustness (mathematics)
Time series
Vibration
Dynamic minimization
Darameter estimation
Synchronization
Chaotic systems
ISSN:0924-090X, 1573-269X
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Shrnutí:This paper proposes a modified dynamic minimization algorithm for parameter estimation of chaotic systems, based on a scalar time series. Comparing with the previous design proposed by Maybhate and Amritkar (Phys. Rev. E 59:284–293, 1999 ), two important new design concepts related to the feedback control and the auxiliary functions for parametric updating laws are introduced. Two different types of estimates can then be derived, and numerical simulations confirm their superior performances to the designs based on the original dynamic minimization algorithm or other existing approaches. Furthermore, a circuit experiment is carried out to demonstrate the robustness and practicability of the proposed design.
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ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-010-9922-0