CONTROL CHAOS IN TRANSITION SYSTEM USING SAMPLED-DATA FEEDBACK

The method for controlling chaotic transition system was investigated using sampled- data . The output of chaotic transition system was sampled at a given sampling rate , then the sampled output was used by a feedbacks subsystem to construct a control signal for controlling chaotic transition system to the origin . Numerical simulations are presented to show the effectiveness and feasibility of the developed controller.     

Partially resolved transition array model in intermediate coupling

The partially resolved transition array (PRTA) model is developed for intermediate coupling. The PRTA model conserves known array properties, yields improved higher moments, systematically accounts for initial level populations, and is computationally efficient compared to detailed line accounting (DLA) methods. Numerical examples show that the PRTA in intermediate coupling reproduces the effects of the electrostatic interaction between spin-orbit split arrays on the spectrum in good agreement with DLA calculations.     

磁耦合双摆的混沌运动

 建立并分析磁耦合双摆的非线性动力学方程，计算其Poincar\'{e}截面图，以解释其典型 的混沌摆动现象.     

Phase transition and scaling in Kuramoto model with high-order coupling

Nonlinear Dynamics - The classical Kuramoto model serves as a useful tool for studying synchronization transitions in coupled oscillators that is limited to the sinusoidal and pairwise...     

CPT磁力仪暗态耦合磁场测量技术

相干粒子数俘获(CPT)磁力仪是通过精确追踪光与原子相互作用下获得的透射信号来计算磁场强度的。针对由于透射信号的方向性衰减特性而造成的系统测量盲区的问题,提出了一种暗态耦合测量方案,通过使用特定频率的调制光场来实现多个暗态的同时激发和耦合测量,基于原子密度矩阵法建立了原子五能级系统模型并进行数值仿真研究,分析了该方案的控制条件和特点。实验结果证明,使用暗态耦合测量技术获得的透射信号幅值可以达到相同条件下单暗态测量时信号幅值的两倍左右,能够有效消除测量盲区,提高透射信号的信噪比,从而进一步提高CPT磁力仪的测量灵敏度。     

Memristive hyperchaos secure communication based on sliding mode control

Nonlinear Dynamics - In order to enhance the chaotic degree of cellular neural network (CNN), the memristive characteristic is combined in CNN, and a five-dimensional memristive CNN hyperchaotic...     

Effect of longitudinal magnetic field on high-speed boundary layer transition

The effect of a longitudinal field on high-speed boundary layer transition has been experimentally investigated.Translated from Izvestiya Akademii Nauk SSSR, Mekhanika Zhidkosti i Gaza, No. 4, pp. 175–177, July–August, 1991.     

Causal coupling inference from multivariate time series based on ordinal partition transition networks

Nonlinear Dynamics - Identifying causal relationships is a challenging yet crucial problem in many fields of science like epidemiology, climatology, ecology, genomics, economics and neuroscience,...     

Heteroclinic motion and energy transfer in coupled oscillator with nonlinear magnetic coupling

In this paper, we consider two coupled oscillators exhibiting both transient chaos and energy transfer from mechanical to electrical oscillators. Melnikov method is applied to these oscillators with linear damping and strongly nonlinear coupling terms in order to study the possibility of existence of chaos and transversal heteroclinic orbits and their control in a dynamical system. The energy transfer is studied using a qualitative measure of the system which can be obtained by computing the energy dissipated in it. At last, the numerical simulation is carried out for this system.     

Chaos transition of the generalized fractional duffing oscillator with a generalized time delayed position feedback

Nonlinear Dynamics - This article is concerned with the study of chaos transition of the duffing oscillator in the presence of fractional-order derivative and third-order polynomial delayed...     

Active feedback control of sound radiation in elastic wave metamaterials immersed in water with fluid–solid coupling

Acta Mechanica Sinica - Due to their potential properties unlike traditional materials and structures, elastic wave metamaterials have received significant interests in recent years. With the...     

Robust synchronization of uncertain chaotic neural networks with randomly occurring uncertainties and non-fragile output coupling delayed feedback controllers

This paper deals with the synchronization control problem for the uncertain chaotic neural networks with randomly occurring uncertainties and randomly occurring control gain fluctuations. By introducing an improved Lyapunov–Krasovskii functional and employing reciprocally convex approach, a delay-dependent non-fragile output feedback controller is designed to achieve synchronization with the help of a drive–response system and the linear matrix inequality approach. Finally, numerical results and its simulations are given to show the effectiveness of the derived results.     

Nonaxisymmetric magnetoelastic coupling natural vibration analysis of annular plates in an induced nonuniform magnetic field

Nonlinear Dynamics - The nonaxisymmetric magnetoelastic nonlinear coupling free vibration study is performed for a conductive thin annular plate in the nonuniform toroidal magnetic field generated...     

Microstructural transition in an ordered set of magnetic spheres immersed in a carrier liquid

This work explores the physics of an ordered set of interacting spheres immersed in a carrier liquid. We present numerical simulations that compute the translational and rotational motion of N interacting spheres based on classical principles of Stokesian dynamics. The spheres are assumed to be made of a magnetizable material, subjected to magnetic and hydrodynamic long range interactions. We explore structure transition using a Lagragian approach of a continuum volume of fluid containing micrometric magnetic particles. We present local maps of particle volume fraction within the calculation Lattice. In this condition, considering the presence and absence of an applied magnetic field, instantaneous snapshots of the local microstructure are taken. Thus, different possibilities of long range interactions are considered. We also complement these results with meaningful statistics of time series obtained through our simulations, such as the correlation time of velocity fluctuations and their self-correlation functions. The data analyzed in the present work sustain the fact that initially ordered neutrally buoyant suspensions have an anisotropic memory-like behavior in the direction of an applied field. It is also observed that particles tend to form small isotropic clusters in the absence of an external field. However, hydrodynamic interactions tend to disperse the particulate phase, avoiding the formation of clusters. This finding suggests that hydrodynamic interactions may play a relevant role on the magnetization dynamics of ferrofluids.