Abstract
The present work introduces an analysis framework to comprehend the dynamics of a 3D plasma model, which has been proposed to describe the pellet injection in tokamaks. The analysis of the system reveals the existence of a complex transition from transient chaos to steady periodic behavior. Additionally, without adding any kind of forcing term or controllers, we demonstrate that the system can be changed to become a multi-stable model by injecting more power input. In this regard, we observe that increasing the power input can fluctuate the numerical solution of the system from coexisting symmetric chaotic attractors to the coexistence of infinitely many quasi-periodic attractors. Besides that, complexity analyses based on Sample entropy are conducted, and they show that boosting power input spreads the trajectory to occupy a larger range in the phase space, thus enhancing the time series to be more complex and random. Therefore, our analysis could be important to further understand the dynamics of such models, and it can demonstrate the possibility of applying this system for generating pseudorandom sequences.
Highlights
Further investigations in nonlinear dynamical systems have contributed to the development and understanding of numerous scientific phenomena
We investigate the dynamics of a plasma perturbation, which consists of three coupled ordinary differential equations that contain three parameters [38]
This paper concentrates on a low-dimensional model [38], that describes the dynamics of pellet injection in tokamaks
Summary
Further investigations in nonlinear dynamical systems have contributed to the development and understanding of numerous scientific phenomena. The investigations of hidden and self-excited chaotic attractors have revealed unexpected results known as coexisting attractors or multistability, which has given the chaotic systems another dimension [27,28]. The system shows other complex behaviors of coexisting multiple symmetric attractors, which can be generated without adding forcing terms or controllers by increasing the power input. On this matter, boosting power input generates extreme multistability, and can enhance the complexity and randomness of the system time series.
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