Controlling chaos to unstable periodic orbits and equilibrium state solutions for the coupled dynamos system

In the case where the knowledge of goal states is not known, the controllers are constructed to stabilize unstable steady states for a coupled dynamos system. A delayed feedback control technique is used to suppress chaos to unstable focuses and unstable periodic orbits. To overcome the topological limitation that the saddle-type steady state cannot be stabilized, an adaptive control based on LaSalle's invariance principle is used to control chaos to unstable equilibrium (i.e. saddle point, focus, node, etc.). The control technique does not require any computer analysis of the system dynamics, and it operates without needing to know any explicit knowledge of the desired steady-state position.     

Stabilizing unstable steady states using extended time-delay autosynchronization

We describe a method for stabilizing unstable steady states in nonlinear dynamical systems using a form of extended time-delay autosynchronization. Specifically, stabilization is achieved by applying a feedback signal generated by high-pass-filtering in real time the dynamical state of the system to an accessible system parameter or variables. Our technique is easy to implement, does not require knowledge of the unstable steady state coordinates in phase space, automatically tracks changes in the system parameters, and is more robust to broadband noise than previous schemes. We demonstrate the controller's efficacy by stabilizing unstable steady states in an electronic circuit exhibiting low-dimensional temporal chaos. The simplicity and robustness of the scheme suggests that it is ideally suited for stabilizing unstable steady states in ultra-high-speed systems. (c) 1998 American Institute of Physics.     

Control of chaotic systems using an on-line trained linear neural controller

We propose a control system including an on-line trained linear neural controller to control chaotic systems. The control system stabilizes a chaotic orbit onto an unstable fixed point without using the knowledge of the location of the point and the local linearized dynamics at the point. Furthermore, the control system can track the stabilized orbit to the unstable fixed point whose location and local dynamics vary slowly with a variation of the system parameter. This paper extends a previous paper (Konishi and Kokame, 1995) for more general situations and improves the neural controller proposed in the previous paper both to simplify the training algorithm and to guarantee the convergence of the neural controller. The stability analysis of the control system reveals that some unstable fixed points cannot be stabilized in the control system. Numerical experiments show that the control system works well for controlling high-dimensional chaotic systems.     

Tailoring steep density profile with unstable points

The mesoscopic properties of a plasma in a cylindrical magnetic field are investigated from the view point of test-particle dynamics. When the system has enough time and spatial symmetries, a Hamiltonian of a test particle is completely integrable and can be reduced to a single degree of freedom Hamiltonian for each initial state. The reduced Hamiltonian sometimes has unstable fixed points (saddle points) and associated separatrices. To choose among available dynamically compatible equilibrium states of the one particle density function of these systems we use a maximum entropy principle and discuss how the unstable fixed points affect the density profile or a local pressure gradient, and are able to create a steep profile that improves plasma confinement.     

Multimode semiconductor laser with selective optical feedback

We study a multimode semiconductor laser subject to moderate selective optical feedback. The steady state of the laser is destabilized by a Hopf bifurcation and exhibits a period-doubling route to chaos. We also show the existence of a heteroclinic connection between a saddle node and an unstable focus that can be associated with experimentally observed multimode low-frequency fluctuations. This heteroclinic connection coexists with a chaotic attractor resulting from the period-doubling process.     

Oscillation death in coupled oscillators

We study dynamical behaviors in coupled nonlinear oscillators and find that under certain conditions, a whole coupled oscillator system can cease oscillation and transfer to a globally nonuniform stationary state [i.e., the so-called oscillation death (OD) state], and this phenomenon can be generally observed. This OD state depends on coupling strengths and is clearly different from previously studied amplitude death (AD) state, which refers to the phenomenon where the whole system is trapped into homogeneously steady state of a fixed point, which already exists but is unstable in the absence of coupling. For larger systems, very rich pattern structures of global death states are observed. These Turing-like patterns may share some essential features with the classical Turing pattern.      

冠状动脉系统高阶滑模自适应混沌同步设计

针对冠状动脉系统混沌同步问题, 系统模型受到有界但未知的不确定干扰条件下, 利用几何齐次性理论和积分滑模面设计高阶滑模自适应控制器, 使响应系统在有限时间内跟踪驱动系统, 该方法无需提前预知扰动边界. 采用Lyapunov理论对闭环系统进行分析并证明该控制器保证该系统能够在有限时间内镇定, 从仿真实验结果可以看出所设计的控制器在不确定干扰的情况下系统具有良好鲁棒性和未知参数的自适应性, 为能够有效治疗心肌梗死等冠状动脉疾病提供了一定的理论依据.     

On-off collective imperfect phase synchronization and bursts in wave energy in a turbulent state

A new type of synchronization, on-off collective imperfect phase synchronization, is found in a turbulent state. In the driver frame the nonlinear wave system can be transformed to a set of coupled oscillators moving in a potential related to the unstable steady wave. In "on" stages the oscillators in different spatial scales adjust themselves to collective imperfect phase synchronization, inducing strong bursts in the wave energy. The interspike intervals display a power-law distribution. In addition to the embedded saddle point, it is emphasized that the delocalization of the master mode also plays an important role in developing the on-off synchronization.     

Stabilization of a class of dynamical complex networks based on decentralized control

This paper deals with a stabilization problem for a class of dynamical complex networks with each node being a general Lur’e system. Based on a Lur’e-Postnikov function and a special decentralized control strategy, the problem of designing a linear feedback controller such that states of all nodes are globally stabilized onto an expected homogeneous state is addressed. A controller design method based on parameter-dependent Lur’e-Postnikov function is proposed in order to reduce the conservativeness and the controller can be constructed via feasible solutions of a certain set of linear matrix inequalities (LMIs). A dynamical network composed of identical Chua's circuits is adopted as a numerical example to demonstrate the effectiveness of the proposed results.     

参数不确定统一混沌系统的鲁棒分数阶比例-微分控制

针对含参数不确定的整数阶统一混沌系统, 提出一种鲁棒分数阶比例-微分(PD^μ)控制. 通过变换将受控统一混沌系统转换成等效被控对象及其等效控制器. 针对等效被控对象, 基于一种改进Monje-Vinagre方法并考虑到求解性能约束方程组的复杂度, 设计了鲁棒PD^μ控制器. 通过基于最小相角边界传递函数和最大增益边界传递函数的设计约束来保证受控统一混沌系统对参数不确定性的鲁棒性能. 数值仿真验证了所提出方法的有效性.