复杂网络外部同步最新研究进展

简单介绍了当前复杂网络外部同步的最新发展,通过回顾复杂网络的研究历程,结合当前的研究热点,具体分析了不连续复杂网络外部同步、两个耦合复杂动力学网络的有限时间外部同步、复杂网络有限时间随机广义外部同步。得出了将来研究复杂网络的一个趋势,以期待为今后复杂网络的研究提供有益借鉴。     

非耗散耦合复杂网络受控同步能力分析

该文研究了非耗散耦合网络的受控同步能力问题。在分析非耗散耦合网络外耦合矩阵特征值分布规律的基础上,给出了非耗散耦合网络的同步控制律。发现外耦合矩阵最大最小特征值之差越小,网络受控同步能力越强,耦合强度越小,网络越有可能通过控制取得同步,但在某些情况下所需要的控制增益绝对值也越大。最后以Lorenz振子小世界网络在混沌轨道上的同步为例对相关结论的有效性进行了验证。     

基于自适应牵制控制的中立型复杂网络渐近同步

针对控制节点未知的中立型耦合复杂网络渐近同步问题,文中设计了更符合工程应用的自适应牵制控制器,并给出了自适应更新律的设计依据.根据广义It?公式、线性矩阵不等式和Lyapunov稳定性理论,给出了中立型耦合复杂网络渐近同步的充分条件.通过数值仿真,计算出同步所需最少牵制节点数,进一步验证了所得渐近同步准则的有效性.     

受激喇曼散射系统构成星型网络的耦合混沌同步

提出了一种实现星型单向激光网络耦合的混沌同步方法。通过适当分离配置各系统的线性项,将其余项作为各节点间的相互耦合函数,研究以四个受激拉曼散射系统构成星型单向激光网络的同步方法。基于Lyapunov定理,构造适当的Lyapunov函数从而实现复杂网络的完全同步。进一步仿真模拟验证了理论分析结果的正确性。     

一种非对称耦合无线传感器网络同步控制模型

无线传感器网络作为一种复杂网络,具有节点众多、拓扑时变等特点。研究传感器网络中的同步问题对于利用节点众多这一特点,实现MIMO协作信息传输、混沌保密通信等应用有着重要的意义。现有对于网络同步的研究大都集中于研究规则网络模型。然而对于无线传感器网络来说,由于无线信道的固有时变特性以及无线传感器网络节点易失效等原因造成了网络拓扑动态变化,从而给传感器网络同步问题的数学建模和分析造成了很大的困难。本文工作受到Belkh[1]工作的启发,提出一种非对称耦合传感器网络同步控制模型。该模型避开了讨论研究具体的网络拓扑结构下的网络同步问题,代之以从控制的角度研究如何改善网络同步性能。理论分析和实验结果表明该模型能够显著提高网络同步化性能。      

多相位粒度萤火虫同步算法

该文针对分布式时间同步算法中,低耦合系数的分组同步问题和大耦合系数的相位振荡失稳现象,提出一种多粒度一致分布式时间同步算法,采用离散多相位粒度模型,将报文交换的相位信息采用多个相位分辨力进行耦合同步,有效地减少了分组现象,加快了同步进程,并提高了算法的执行效率。最后利用仿真实验和传统的MS仿生算法进行对比实验,验证了其在非全连接网络中,可以取得比传统算法更好的同步效果。     

基于ZigBee节点的按需时间同步算法

简要阐述近年来无线传感网络时间同步（TPSN）算法的发展概况和影响无线传感器网络时间同步的因素,结合无线传感网络中路由节点与终端节点的特点,提出一种融合了参考广播同步（RBS）与TPSN算法设计,在保持同步精确度前提下,整个网络的功耗大大降低。通过实验采集到的数据分析了协议的可行性,证明该算法较适合于对节点密度高,终端节点较多的无线网络中,如工业有害气体的检测。     

基于分数阶CCVNN的混合控制投影同步问题研究

分数阶微积分具有历史依赖性、全局性以及遗传性,将其引入神经网络能够更准确地刻画神经元的记忆、认知、决策等特征。耦合复值神经网络（Coupled Complex Valued Neural Networks,简称CCVNN）可以表现出子网络之间的信息交互与协作,使得分数阶系统表现出更加复杂而丰富的动力学行为。本文结合分数阶Lyapunov稳定性理论、神经网络系统理论以及特殊函数的性质,在Caputo分数阶导数意义下分别讨论CCVNN的同步问题。鉴于耦合复值网络具有高效处理二维数据的能力,本文研究分数阶复值神经网络的投影同步问题,结合M-矩阵理论建立保证网络实现Mittag-Lefflfler投影同步的充分条件。最后,采用分数阶微积分的性质和调和级数的发散性详细证明网络的自适应同步问题,通过提供相应的数值实例来验证理论分析中设计的控制策略和建立的同步准则。     

两个带有已知或未知参数的复杂网络的改进函数投影同步

近年来复杂网络在科学与工程各个领域受到了广泛关注,其中复杂网络同步问题是复杂网络研究的热点之一。该文研究两个复杂网络实现改进函数投影同步的方法。分别基于复杂网络模型参数已知和未知两种情况,利用李雅普诺夫稳定性理论和自适应控制技术,设计自适应同步控制器,使两个复杂网络达到改进函数投影同步。最后分别基于这两种情况利用数值仿真验证所提方法的有效性。     

一种PCM/FM接收机的定时同步设计和实现

时钟同步是接收机的关键问题,传统模拟解调灵活性差,调试复杂。针对测控中常用的PCM/FM体制,介绍了一种全数字接收机的定时同步方法,采用数字转换跟踪环估计定时误差,通过内插计算和反馈控制采样时钟完成误差校正。同步计算全部由软件实现,设计灵活。Matlab仿真及VHDL代码的硬件实测结果表明,该方法同步时间快、定时精度高,适合FPGA实现。     

Global Synchronization and State Tuning in Asymmetric Complex Dynamical Networks

A strategy to control the complex dynamical networks for global synchronization as well as to tune their synchronous states is presented based on linear state feedback controllers. The synchronous state can be changed from one system to other similar system just by choosing a suitable tuning matrix. Especially, some of the criteria are expressed in normal inequalities instead of matrix inequalities. Simulations are also done to verify the theoretical results.      

Pinning a Complex Delayed Dynamical Network to a Homogenous Trajectory

Time delay exists in many fields, such as biology, neural network, mechanics, ecology, and so on. It is important for us to investigate the control of interconnected time-delay systems. In this brief, we propose two schemes to pin a complex delayed dynamical network to a homogenous trajectory. In particular, we prove that the delayed dynamical network is asymptotically synchronized with linear feedback control, and it is exponentially asymptotically synchronized with adaptive feedback controllers. We also find that the number of pinned nodes satisfies an inequality for synchronization. Additionally, the coupling matrix is not necessarily symmetric, and the pinned nodes can randomly be selected. Moreover, the linear feedback gain need not be large. Finally, two well-known network models are provided as illustrative examples to confirm the effectiveness of the technique.     

Asymptotic trajectory tracking of manipulators using uncalibrated visual feedback

To implement a position-based visual feedback controller for a manipulator, it is necessary to calibrate the homogeneous transformation matrix between its base frame and the vision frame besides intrinsic parameters of the vision system. The accuracy of such a calibration greatly affects the control performance. Substantial efforts must be made to obtain a highly accurate transformation matrix. In this paper, we propose an adaptive visual feedback controller for manipulators when the homogeneous transformation matrix is not calibrated. It is assumed that the vision system can measure the 3D position and orientation of the manipulator in real-time. Based on an important observation that the unknown transformation matrix can be separated from the visual Jacobian matrix, we propose an adaptive algorithm, similar to the model-based adaptive algorithm, to estimate the unknown matrix online. The use of the proposed visual feedback controller greatly simplifies the implementation of a manipulator-vision workcell. This controller is especially useful when such a pre-calibration is not possible. It is proved by Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results are included to demonstrate performance of this adaptive visual feedback controller.     

Transmission Subspace Tracking for MIMO Systems With Low-Rate Feedback

This paper describes a feedback algorithm for tracking the dominant subspaces of continuously time-varying channels in multiantenna communication systems. The nature of the problem is quantization of subspaces. It is well known that subspaces can be mathematically modeled as points in a Grassmann manifold. We model the variations between the dominant subspaces of channels at adjacent time instants to be along geodesics in the Grassmann manifold. Instead of quantizing the subspaces themselves, we propose to quantize the geodesic trajectory connecting two subspaces. More specifically, we quantize a key entity that characterizes a geodesic arc: the velocity matrix, which resembles angular speed in a one-dimensional complex space. Two techniques are proposed for quantizing the velocity matrix of the geodesic. In the first, a 1-bit feedback is utilized to indicate the preferred sign of a random velocity matrix of the geodesic. In the other, the velocity matrix is quantized using a Gaussian vector quantization codebook. Numerical results show that the performance of the proposed 1-bit feedback algorithm is better than a previously proposed Grassmannian subspace packing scheme at low-to-medium Doppler frequencies and better than a gradient sign feedback scheme at all Doppler frequencies. In our simulations, the Gaussian vector quantization algorithm is always better than the 1-bit feedback algorithm.     

一种基于LMI的离线预测控制算法

针对预测控制滚动优化命题的在线计算任务大，本文提出了一种基于LMI的离线预测控制算法，通过离线求解线性矩阵不等式优化命题构造分段线性反馈控制律，在线运行时只需实施满足条件的反馈控制律，极大提高在线计算效率。仿真结果表明该算法的有效性。     

Passivity-based Control for Markovian Jump Systems via Retarded Output Feedback

This paper is concerned with the problem of passivity-based control for Markovian jump systems via retarded output feedback controllers. A delay-dependent passivity criterion is obtained in terms of linear matrix inequalities. Based on this, a sufficient condition is proposed for the design of a retarded output feedback controller which ensures that the closed-loop system is passive. By using the sequential linear programming matrix method, a desired retarded output feedback controller can be constructed. Numerical examples are provided to demonstrate the advantage and effectiveness of the proposed method.     

基于Riccati型方程与遗传算法的容错控制研究

通过求解Riccati型方程可以设计一个状态反馈控制器,可以使MIMO系统对某些故障具有一定的容错性能。针对系统的传感器故障,采用遗传算法对求解Riccati型方程时所用到的初始矩阵进行全局优化,得到系统的最佳反馈阵。对某型导弹的简化模型进行仿真试验,结果证明上述方法的有效性。对于执行器故障情形,也可以采取类似方法。     

Design of multivariable systems using unity-rank state feedback: further results

The letter describes three applications of the degrees of freedom in the design of a unity-rank state feedback matrix for pole assignment in a multivariable system. These include sensitivity reduction of closed-loop poles and restrictions on the magnitudes of feedback gains and control inputs. The method is illustrated by a numerical example.     

超混沌复系统的自适应广义组合复同步及参数辨识

该文针对含未知参数的异结构超混沌复系统,基于自适应控制及Lyapunov稳定性理论,提出一种新的自适应广义组合复同步方法 (GCCS)。首先给出广义组合复同步的定义,将驱动-响应系统的同步问题转化为误差系统零解的稳定性问题;然后从理论上设计了非线性反馈同步控制器及参数辨识更新律,并引入误差反馈增益,以控制同步的收敛速度;最后以超混沌复Lorenz系统、超混沌复Chen系统、超混沌复L系统的广义组合复同步与参数估计为例,从数值仿真角度验证了所提方法的正确性和有效性。     

An Efficient Multimode Quantized Precoding Technique for MIMO Wireless Systems

Multimode quantized precoding (QP) can provide full diversity gain or high capacity gain by adapting the number of substreams, as well as the precoding matrix, according to the instantaneous channel condition with low-rate feedback. Conventional multimode QP (MM-QP), however, does not consider the adaptive rate allocation among substreams; thus, it cannot have the additional gain by adaptive modulation. Furthermore, it is computationally complex since exhaustive matrix inversions are required to determine the optimal mode. In this paper, we propose an efficient MM-QP system that improves the performance of a conventional system in terms of error rate and has a lower computational complexity than the conventional system. First, we define the rate-partitioning vector as the mode and control the rate among substreams and the number of substreams according to the channel instantaneous condition. Second, to reduce the computational complexity for the receiver to determine the optimal mode, the simplified mode-selection technique using estimates of the modal metric is proposed. In the proposed mode-selection technique, the optimal mode can be obtained by several multiplication and division operations. Finally, the mode-reduction technique eliminating the less-frequently used modes is proposed, which leads to a significant reduction of the feedback information with negligible performance loss. In numerical experiments, it was verified that the proposed MM-QP system gives a better error-rate performance than the conventional system, with much less computational complexity for the same amount of feedback information.