Abstract

The synchronization between chaotic systems implemented in similar ways—e.g., computer models or circuits—is a well-investigated topic. Nevertheless, in many practical applications, such as communication, identification, machine sensing, etc., synchronization between chaotic systems of different implementation types—e.g., between an analog circuit and computer model—might produce fruitful results. In this research, we study the synchronization between a circuit modeling the Rössler chaotic system and a computer model using the same system. The theoretical possibility of this kind of synchronization is proved, and experimental evidence of this phenomenon is given with special attention paid to the numerical methods for computer model simulation. We show that synchronization between a circuit with uncertain parameters and a computer model is possible, and the parameters obtained from the synchronized computer model are in high correspondence with the circuit element specification. The obtained results establish the possibility of using adaptive generalized synchronization for the parameter identification of real systems. It was also found that Heun’s method yielded the most accurate results in synchronization among second-order numerical integration methods. The best among the first-order methods appears to be the Euler–Cromer method, which can be of interest in embedded applications.

Highlights

  • The synchronization of dynamical systems is a widely used principle in communication, measurement and control

  • We found that the complete synchronization (CS) between digital and analog implementations of the same chaotic system meets notable restrictions due to truncation and round-off errors in a computer model, noise and imperfect operation of the circuit and the existence of signal-corrupting barriers such as analog-to-digital converters (ADCs) and digital-to-analog converters (DAC) in a coupling channel [22,23]

  • According to Conjecture 1, the synchronization error tends to vanish if the system difference becomes negligible

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Summary

Introduction

The synchronization of dynamical systems is a widely used principle in communication, measurement and control. We found that the CS between digital and analog implementations of the same chaotic system meets notable restrictions due to truncation and round-off errors in a computer model, noise and imperfect operation of the circuit and the existence of signal-corrupting barriers such as analog-to-digital converters (ADCs) and digital-to-analog converters (DAC) in a coupling channel [22,23] These results forced us to conduct the current research, in which we focus on the adaptive generalized synchronization between the analog and numeric implementation of the same system. Data obtained from a designed circuit and some program codes in MATLAB can be found in the authors’ repository [24]

Terms and Definitions
Synchronization between Systems Implemented in Different Ways
Adaptive Complete Synchronization between Numerical Models
Adaptive Generalized Synchronization between Numerical Models
Circuit Implementation
Circuit Operation
Adaptive Generalized Synchronization between Circuit and Numerical Model with
Tracking an Additional Parameter in Adaptive Generalized Synchronization
Findings
Conclusions
Full Text
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