Synchronization Based Approach for Estimating All Model Parameters of Chaotic Systems

Abstract

The problem of dynamic estimation of all parameters of a model representing chaotic and hyperchaotic systems using information from a scalar measured output is solved. The variational calculus based method is robust in the presence of noise, enables online estimation of the parameters and is also able to rapidly track changes in operating parameters of the experimental system. The method is demonstrated using the Lorenz, Rossler chaos and hyperchaos models. Its possible application in decoding communications using chaos is discussed.

13 pages, 4 figures

References in corpus (3)

• Use of synchronization and adaptive control in parameter estimation from a time series
• Designing coupling that guarantees synchronization between identical chaotic systems
• Synchronization of chaotic systems: Transverse stability of trajectories in invariant manifolds

Cited by in corpus (3)

• Estimation of System Parameters and Predicting the Flow Function from Time Series of Continuous Dynamical Systems
• Estimation of System Parameters in Discrete Dynamical Systems from Time Series
• Parameter estimation, nonlinearity and Occam's razor