Theoretical and experimental aspects of chaos control by time-delayed feedback

We review recent developments for the control of chaos by time-delayed feedback methods. While such methods are easily applied even in quite complex experimental context the theoretical analysis yields infinite-dimensional differential-difference systems which are hard to tackle. The essential ideas for a general theoretical approach are sketched and the results are compared to electronic circuits and to high power ferromagnetic resonance experiments. Our results show that the control performance can be understood on the basis of experimentally accessible quantities without resort to any model for the internal dynamics.     

同轴插板式相移器数值模拟与实验研究

 根据同轴插板式相移器的基本工作原理,对该相移器进行了数值模拟与优化设计,并重点研究了其结构工艺和相移控制方式。在此基础上研制了一个中心频率为4.1 GHz的相移器模型,并通过矢量网络分析仪进行了实验测量。测量结果表明：在4.0～4.2 GHz的频带范围内,该相移器可实现90°的相移量,相移量化精度为1°,相移精度为±１０°,相移器插损1.5 dB。     

同轴插板式相移器数值模拟与实验研究

根据同轴插板式相移器的基本工作原理,对该相移器进行了数值模拟与优化设计,并重点研究了其结构工艺和相移控制方式。在此基础上研制了一个中心频率为4.1 GHz的相移器模型,并通过矢量网络分析仪进行了实验测量。测量结果表明：在4.0～4.2 GHz的频带范围内,该相移器可实现90°的相移量,相移量化精度为1°,相移精度为±１０°,相移器插损1.5 dB。     

Generalised synchronisation of spatiotemporal chaos using feedback control method and phase compression

Coupled map lattices are taken as examples to study the synchronisation of spatiotemporal chaotic systems. First, a generalised synchronisation of two coupled map lattices is realised through selecting an appropriate feedback function and appropriate range of feedback parameter. Based on this method we use the phase compression method to extend the range of the parameter. So, we integrate the feedback control method with the phase compression method to implement the generalised synchronisation and obtain an exact range of feedback parameter. This technique is simple to implement in practice. Numerical simulations show the effectiveness and the feasibility of the proposed program.     

Effect of noise on chaos synchronization in time-delayed systems: Numerical and experimental observations

We discuss the constructive role of noise (white and colored) in chaos synchronization in time-delayed systems. We first numerically investigate noise-induced synchronization (NIS) between two identical uncoupled Ikeda and Mackey–Glass systems. We find that synchronization occurs above a critical noise intensity that differs for different colors of noise. Synchronization onset is characterized by the value of the maximum transverse Lyapunov exponent. We then discuss the enhancement of chaos synchronization between two time-delayed systems when they are coupled unidirectionally. The effect of parameter mismatch for NIS is described in detail. We provide experimental evidence of NIS for a Mackey–Glass-like system in an electronic circuit using different colors of noise. An integration scheme for time-delayed systems in the presence of additive white and colored noise is discussed.     

Target-oriented chaos control

Designing intervention methods to control chaotic behavior in dynamical systems remains a challenging problem, in particular for systems that are difficult to access or to measure. We propose a simple, intuitive technique that modifies the values of the state variables directly toward a certain target. The intervention takes into account the difference to the target value, and is a combination of traditional proportional feedback and constant feedback methods. It proves particularly useful when the target corresponds to the equilibrium of the uncontrolled system, and is available or can be estimated from expert knowledge (e.g. in biology and economy).     

Prediction-based control of chaos

Pyragas proposes a practically useful control method, called delayed feedback control, for control of chaos. Conditions for (local) stabilization by the delayed feedback control, however, are more restricted than those by the OGY method. In order to overcome this problem, we propose a novel control method, called a prediction-based feedback control, for discrete-time chaotic systems. Moreover, we give necessary and sufficient conditions for exponential stabilization of fixed points by the proposed method.     

Fluctuations and the energy-optimal control of chaos

We compute the pressure of a finite-density quark-gluon plasma at zero temperature to leading order in hard-thermal-loop perturbation theory, which includes the fermionic excitations and Landau damping. The result is compared with the weak-coupling expansion for finite positive chemical potential &mgr; through order alpha(2)(s) and with a quasiparticle model with a mass depending on &mgr;.     

Impulsive control of stochastic systems with applications in chaos control, chaos synchronization, and neural networks

Real systems are often subject to both noise perturbations and impulsive effects. In this paper, we study the stability and stabilization of systems with both noise perturbations and impulsive effects. In other words, we generalize the impulsive control theory from the deterministic case to the stochastic case. The method is based on extending the comparison method to the stochastic case. The method presented in this paper is general and easy to apply. Theoretical results on both stability in the pth mean and stability with disturbance attenuation are derived. To show the effectiveness of the basic theory, we apply it to the impulsive control and synchronization of chaotic systems with noise perturbations, and to the stability of impulsive stochastic neural networks. Several numerical examples are also presented to verify the theoretical results.     

Progress in the control of chaos

In this review, we summarize several of the key contributions made over the past 5 years to the control of chaotic dynamical systems. The idea that chaotic systems can in fact be controlled may be counter-intuitive; after all they are unpredictable in the long term. Nevertheless, numerous theorists have independently developed methods which can be applied to chaotic systems, and many experimentalists have demonstrated that physical chaotic systems respond well to both simple and sophisticated control strategies. The great bulk of these researchers have restricted their study to low-dimensional systems, and correspondingly we critique this work at length. Most recently, a few researchers have proposed control techniques for application to high- or infinite-dimensional systems, and we describe this work in some detail as well.     

电阻电容分路的约瑟夫森结中阵发性混沌及混沌控制的计算机模拟

通过计算机模拟研究了电阻电容分路的约瑟夫森结中的混沌行为,给出了结电压随阻尼参数及偏置直流电流变化的分岔图,从而展示了混沌产生的方式及混沌出现的参数区间,并基于弱周期扰动理论提出了控制RCSJJ中混沌的方案,模拟结果证明了该方案的有效性.     

Chaos and transient chaos in an experimental nonlinear pendulum

Pendulum is a mechanical device that instigates either technological or scientific studies, being associated with the measure of time, stabilization devices as well as ballistic applications. Nonlinear characteristic of the pendulum attracts a lot of attention being used to describe different phenomena related to oscillations, bifurcation and chaos. The main purpose of this contribution is the analysis of chaos in an experimental nonlinear pendulum. The pendulum consists of a disc with a lumped mass that is connected to a rotary motion sensor. This assembly is driven by a string-spring device that is attached to an electric motor and also provides torsional stiffness to the system. A magnetic device provides an adjustable dissipation of energy. This experimental apparatus is modeled and numerical simulations are carried out. Free and forced vibrations are analyzed showing that numerical results are in close agreement with those obtained from experimental data. This analysis shows that the experimental pendulum has a rich response, presenting periodic response, chaos and transient chaos.     

预测反馈法控制双向闭环时空混沌系统的理论及实验

预测反馈控制方法可以用于控制时空混沌系统,该方法是在耦合映象格子中的每个格点处加入局部预测反馈控制器.本文以双向环形Henon耦合映象格子为例,在理论上给出了将系统控制到不稳定不动点的充分条件,并通过数值计算及电路仿真实验证实该方法的有效性.     

双馈风力发电机混沌运动分析及滑模控制混沌同步

以双馈风力发电机组(DFIG)为研究对象,推导了其dq轴数学模型. 根据某2MW主流双馈电机实际参数,论证了在某些参数及工作条件下会出现混沌运动. 基于主动控制思想,设计了一种主动滑模控制器,使得从任意初始条件出发均能保证系统稳定. 基于Lyapunov稳定性理论分析了系统稳定性. 以双馈电机模型为例进行数值仿真验证,较快的实现了混沌系统同步. 仿真结果表明该控制方法具有良好的鲁棒性和稳定性. 关键词： 风力发电 双馈风力发电机组(DFIG) 混沌控制和滑模控制 同步     

Optimal chaos control through reinforcement learning

A general purpose chaos control algorithm based on reinforcement learning is introduced and applied to the stabilization of unstable periodic orbits in various chaotic systems and to the targeting problem. The algorithm does not require any information about the dynamical system nor about the location of periodic orbits. Numerical tests demonstrate good and fast performance under noisy and nonstationary conditions. (c) 1999 American Institute of Physics.