基于改进的多轴差分吸收光谱层析技术的烟羽浓度峰重建

建立了被动多轴差分吸收光谱层析系统,实现烟羽气体的时空浓度分布测量,分别采用传统的同步迭代重建算法(SIRT)和改进的SIRT对测量数据进行了重建分析,克服了一些实际测试中不能获 取大量投影数据或投影分布不均匀、存在噪声的问题,精确地重建出大气痕量气体的二维空间分布．在不同的模型及评价指标下,通过数值模拟对两种重建算法的效果进行比较,改变改进的SIRT算法中的松弛因子,在5500次的迭代过程中,指标d从0.435降到了0.044,指标r从0.376降到了0.044,改进的SIRT算法具有更好的重建效果．外场重建试验中成功重建了大气痕量气体的二维空间．     

欧洲第四代自由电子激光源投入使用

<正>在当代科技领域,对高亮度、短脉冲、可调谐先进激光源的需求越来越多。先进的激光源,对新材料、生命科学、新药研发等领域的研究将不可或缺。位于意大利雅斯特(Trieste)的同步激光加速器(Sincrotrone)提供的高亮度、短脉冲同步光源,可在原子和分子层面详尽研究物质的表面结构和内在行为,是电子科学、环境保护、药物开发、医疗诊断、工程技术和纳米科技研发的     

具有界时滞和分布时滞的反应扩散神经网络的指数同步

本文研究了一类具有界时滞和分布时滞的反应扩散神经网络的状态变量在边界为零的条件下驱动系统和响应系统的指数同步性,得到了其驱动系统和响应系统指数同步的充分条件。     

Synchronization of different chaotic systems via active radial basis functions sliding mode controller

This paper presents a new method to synchronize different chaotic systems with disturbances via an active radial basis function （RBF） sliding controller. This method incorporates the advantages of active control, neural network and sliding mode control. The main part of the controller is given based on the output of the RBF neural networks and the weights of these single layer networks are tuned on-line based on the sliding mode reaching law. Only several radial basis functions are required for this controller which takes the sliding mode variable as the only input. The proposed controller can make the synchronization error converge to zero quickly and can overcome external disturbances. Analysis of the stability for the controller is carried out based on the Lyapunov stability theorem. Finally, five examples are given to illustrate the robustness and effectiveness of the proposed synchronization control strategy.     

Passive adaptive control of chaos in synchronous reluctance motor

The performance of synchronous reluctance motor （SynRM） degrades due to chaos when its systemic parameters fall into a certain area. To control the undesirable chaos in SynRM, a passive control law is presented in this paper, which transforms the chaotic SynRM into an equivalent passive system. It is proved that the equivalent system can be asymptotically stabilized at the set equilibrium point, namely, chaos in SynRM can be controlled. Moreover, in order to eliminate the influence of undeterministic parameters, an adaptive law is introduced into the designed controller. Computer simulation results show that the proposed controller is very effective and robust against the uncertainties in systemic parameters. The present study may help to maintain the secure operation of industrial servo drive system.     

A unified approach to fuzzy modelling and robust synchronization of different hyperchaotic systems

In this paper, a Takagi Sugeno （T-S） fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems. The T S fuzzy models with a small number of fuzzy IF-THEN rules are employed to represent many typical hyperchaotic systems exactly. The benefit of employing the T-S fuzzy models lies in mathematical simplicity of analysis. Based on the T-S fuzzy hyperchaotic models, two fuzzy controllers arc designed via parallel distributed compensation （PDC） and exact linearization （EL） techniques to synchronize two identical hyperchaotic systems with uncertain parameters and two different hyperchaotic systems, respectively. The sufficient conditions for the robust synchronization of two identical hyperchaotic systems with uncertain parameters and the asymptotic synchronization of two different hyperchaotic systems are derived by applying the Lyapunov stability theory. This method is a universal one of synchronizing two identical or different hyperchaotic systems. Numerical examples are given to demonstrate the validity of the proposed fuzzy model and hyperchaotic synchronization scheme.     

Adaptive generalized projective synchronization of two different chaotic systems with unknown parameters

This paper presents a general method of the generalized projective synchronization and the parameter identification between two different chaotic systems with unknown parameters. This approach is based on Lyapunov stability theory, and employs a combination of feedback control and adaptive control. With this method one can achieve the generalized projective synchronization and realize the parameter identifications between almost all chaotic （hyperchaotic） systems with unknown parameters. Numerical simulations results are presented to demonstrate the effectiveness of the method.     

Synchronization of stochastically hybrid coupled neural networks with coupling discrete and distributed time-varying delays

A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed, which is composed of constant coupling, coupling discrete time-varying delay and coupling distributed timevarying delay. All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion, which reflects a more realistic dynamical behaviour of coupled systems in practice. Based on a simple adaptive feedback controller and stochastic stability theory, several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays. Finally, numerical simulations illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.     

复系统Julia集的同步

非线性系统中的分形集——Julia集, 在工程技术中有着十分重要的应用,定义了不同系统间的Julia集同步的概念, 并引入一种非线性耦合的方法, 对同一系统不同参数的Julia集进行了有效的同步.并以多项式形式和三角函数形式的Julia集同步为例验证了该方法的有效性.     

两台独立飞秒钛宝石振荡器的高精度主动同步研究

对两台独立钛宝石飞秒振荡器的高精度主动同步进行了研究.实验中共采用三套锁相环对它们输出的激光脉冲进行了主动同步控制，最终得到了时间抖动低于30fs的同步精度；由于通过计算机智能监控两台振荡器的相对腔长变动，使得高精度同步维持的时间高达40min.