Abstract

Chaotic systems are one of the most significant systems of the technological period because their qualities must be updated on a regular basis in order for the speed of security and information transfer to rise, as well as the system's stability. The purpose of this research is to look at the special features of the nine-dimensional, difficult, and highly nonlinear hyperchaotic model, with a particular focus on synchronization. Furthermore, several criteria for such models have been examined; Hamiltonian, synchronizing, Lyapunov expansions, and stability are some of the terms used. The geometrical requirements, which play an important part in the analysis of dynamic systems, are also included in this research due to their importance. The synchronization and control of complicated networks' most nonlinear control is important to use and is based on two major techniques. The linearization approach and the Lyapunov stability theory are the foundation for attaining system synchronization in these two ways.

Highlights

  • Introduction eLyapunov method, which is referred to as the Lyapunov stability criterion, uses a Lyapunov V(x) function that is similar to the potential function of classical dynamics

  • Contribution (i) We have proposed the system which clearly depicts that while increasing the parameter, the corresponding values of are decreased (ii) From a detailed analysis and results, we have achieved featured for the 9-dimensional, complex, and highly nonlinear hyperchaotic model which has been executed to make a model more dynamic (iii) For various models, several criteria have been examined, such as Hamiltonian, Synchrony, Lyapunov expansion, and stability

  • E complex variables were calculated using the traditional Lu Model. It may be deduced from the given model that the model was created by replacing actual variables. is is seen in equations (4) and (5). e system has been proposed and achieved at large sizes

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Summary

Contribution (i)

We have proposed the system which clearly depicts that while increasing the parameter, the corresponding values of are decreased (ii) From a detailed analysis and results, we have achieved featured for the 9-dimensional, complex, and highly nonlinear hyperchaotic model which has been executed to make a model more dynamic (iii) For various models, several criteria have been examined, such as Hamiltonian, Synchrony, Lyapunov expansion, and stability

Structure
Hamiltonian Dynamics
Equilibria
Dissipation
Lyapunov Exponents
Model of a Weighted-Complex Network
Numerical Results and Discussion
Attractors of a Proposed System
Conclusions
Full Text
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