一个计算网络可靠度的递归算法

给出一个计算网络可靠度的有效算法,该算法的特点是结合概率论的有关知识和布尔代数运算：递归地调用一个简单、有效的概率公式来计算网络可靠度。该算法易于在计算机上操作和实现,从而适用于大型网络可靠度的定量计算。最后通过实例验证所给算法的有效性。     

具有区间时变时滞的离散Markov跳变系统鲁棒H∞控制

研究一类具有区间时变时滞的离散时间不确定Ｍａｒｋｏｖ跳变系统的时滞相关鲁棒H_∞ 控制问题．通过构造新的ＬｙａｐｕｎｏｖＫｒａｓｏｖｓｋｉｉ泛函,基于有限和不等式方法设计状态反馈控制器,使得闭环系统在容许不确定性下鲁棒稳定,且对能量有界的输入噪声满足一定输入输出H_∞ 增益．在新控制器存在条件中未引入任何自由变量矩阵,使之可更为有效地求解．基于锥补线性化的迭代算法可有效求解H_∞ 次优控制器．数值算例表明了所提出方法的有效性．     

Stability of nonlinear hybrid dynamical systems with time delay via sum of squares decomposition

Considering an infinite number of eigenvalues for time delay systems, it is difficult to determine their stability. We have developed a new approach for the stability test of time delay nonlinear hybrid systems. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are found, stability’s analysis of the system is straight-forward. In this paper both delay-independent and delay-dependent stability tests are proposed, based on the construction of appropriate Lyapunov-Krasovskii functionals. The methodology is based on the sum of squares decomposition of multivariate polynomials and the algorithmic construction is achieved through the use of semidefinite programming. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be computationally infeasible to solve. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Finally simulation results show the correctness and validity of the designed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors wish to express their thanks to Dr. A. Papachristodoulou and Dr. M. Peet for their helpful comments and suggestions. Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received the B.S. degree in Electrical Engineering from University of Tabriz in 1998 and the M.Sc. degree in Control Engineering from University of Tabriz in 2001. He received the Ph.D. degree in Control Engineering from University of Tabriz in 2007. He is now an Assistant Professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include Hybrid dynamical systems, Stability of systems, Time delay systems, Robot path planning. Sohrab Khanmohammadi received the B.S. degree in Industrial Engineering from Sharif University, Iran in 1977 and the M.Sc. degree in Automatic from University Paul Sabatie, France in 1980 and the Ph.D. degree in Automatic from National University, ENSAE, France in 1983. He is now a Professor of Electrical Engineering at University of Tabriz. His research interests are Fuzzy control, Artificial Intelligence applications in control and simulation on industrial systems and human behavior. Gasem Alizadeh was born in Tabriz, Iran in 1967. He received the B.S. degree in Electrical Engineering from Sharif University, Iran in 1990 and the M.Sc. degree from Khajeh Nasir Toosi University, Iran in 1993 and the Ph.D. degree in Electrical Engineering from Tarbiat Modarres University, Iran in 1998. From 1998, he is a Member of University of Tabriz in Iran. His research interests are robust and optimal control, guidance, navigation and adaptive control. Ali Aghagolzadeh was born in Babol, Iran. He received the B.S. degree in Electrical Engineering in 1985 from University of Tabriz, Tabriz, Iran, and the M.Sc. degree in Electrical Engineering in 1988 from the Illinois Institute of Technology, Chicago, IL. He also attended the School of Electrical Engineering at Purdue University in August 1998 where he was also employed as a part-time research assistant and received the Ph.D. degree in 1991. He is currently an Associate Professor of Electrical Engineering at University of Tabriz, Tabriz, Iran. His research interests include digital signal and image processing, image coding and communication, computer vision, and image analysis.     

可调谐钛宝石双波长激光在β－BaB2O4晶体中和频

本文用矩阵光学推导出了相位共轭腔的热稳条件。     

基于C-V2X的车路协同自动驾驶关键技术与应用

随着车联网技术的演进,自动驾驶在单车智能的基础上,又有了新的发展形态——车路协同自动驾驶。通过“人-车-路-云”深度融合形成的一体化复杂信息物理系统（cyber physical system,CPS）,可以与自动驾驶车辆实现协同感知、协同决策规划甚至协同控制,提升自动驾驶安全性,帮助克服各类复杂交通环境。首先介绍了车路协同的复杂信息物理系统的概念内涵和总体架构,并提出了车路协同自动驾驶的一系列典型应用场景、技术原理、C-V2X(cellular vehicle-to-everything)性能要求、车路协同系统功能与性能要求,可以为下一阶段智能网联汽车与智能交通的深度融合发展提供参考和解决思路。     

一种基于深度学习的高轨卫星CEI信号频率估计算法

针对高轨卫星连线干涉测量(Connected Element Interferometry,CEI)信号的高精度频率估计这一难题,建立了CEI中的正弦信号频率估计模型。设计了基于深度学习框架的CEI信号频率估计算法,将算法划分为基于前馈深度神经网络的频率表征模块和基于卷积神经网络的频率计算及估计模块,在此基础上设计了各模块的具体结构和学习训练流程。对于算法的核心模块进行了仿真实验验证,并将所提算法与前人的相关算法进行了比较与分析,证明了该算法的有效性、稳定性和优越性。     

Fully distributed consensus for fuzzy multiagent systems with jointly connected topology

This paper investigates the problem of fully distributed consensus for polynomial fuzzy multiagent systems (MASs) under jointly connected topologies. First, a polynomial fuzzy modeling method is presented to characterize the error dynamics that is constructed by one leader and multiple followers. Then, using the relative state information and the agents' dynamics, a distributed adaptive protocol is designed to guarantee that MASs under jointly connected topologies can achieve consensus in a fully distributed fashion. Utilizing the Lyapunov technique, a relaxed sufficient criterion is proposed to ensure consensus for fuzzy MASs under jointly connected topologies. Moreover, the adaptive coupling weights between neighboring agents can converge to certain values. The derived condition is transformed into a sum-of-squares form, which can be solved numerically. We provide an example to illustrate the proposed distributed adaptive consensus technique's validity.     

交叉口混合交通流微观控制模型

为构建智能网联汽车(CAV)和有人驾驶汽车(HDV)混合通行情况下的交叉口通行机制与控制方法, 本文提出CAV专用道条件下交叉口协同通行模型. 首先, 设计CAV专用道条件下的交叉口布置, 对交叉口进行网格化处理,将CAV通行时隙和HDV绿灯相位对交叉口某部分网格某时段的占用统一到交叉口时空资源描述框架下; 其次, 建立兼顾CAV与HDV的交叉口时空网格资源分配模型, 构建自适应信号灯控制算法和CAV轨迹规划算法; 再次, 以车辆最小延误为目标进行自适应信号灯配时优化和CAV轨迹优化; 最后, 选取广州某典型交叉口建立仿真实验对所提方法的有效性进行了验证.     

具有非匹配扰动的非线性变参数系统模型参考跟踪控制

本文研究了一类含有非匹配扰动的非线性变参数系统的跟踪控制问题.首先,设计非线性扰动观测器用于估计系统所受到的未知扰动.其次,在前馈–反馈跟踪控制器中引入扰动补偿控制项,提出一种基于扰动观测器的跟踪控制策略.利用依赖于状态和时变参数的线性矩阵不等式,导出保证闭环系统输入–状态稳定的充分条件,进而运用平方和凸优化技术解析地构造出扰动观测器和跟踪控制器.通过理论证明,所设计的控制策略能够实现非线性变参数系统输出对参考模型输出的跟踪,消除输出通道中非匹配扰动的影响.最后,由数值仿真例子验证了所提方法的有效性.     

基于雨雾分离处理和多尺度网络的图像去雨方法

雨带来的雨条纹和雨雾会降低户外拍摄图像的质量,为了去除雨雾对图像的影响,提出了一种基于雨雾分离处理和多尺度卷积神经网络的图像去雨方法。首先利用导向滤波将雨线和图像细节信息提取到高频层,雨雾和背景信息则分离到低频层;然后构建多尺度卷积神经网络来去除高频层中的雨线,网络中融入多个稠密连接模块以提升特征提取的准确性;其次构建多层特征融合的轻量级去雾网络来去除低频层中的雨雾,采用参数一体化结构避免了估计多个大气散射模型参数导致的次优解;最后再结合处理后的高低频结果还原出清晰图像。在多个合成的雨雾数据集以及真实自然场景图像上进行测试,定性和定量结果表明,提出的方法在去除雨雾影响的同时较好地保留了色彩信息,和近年的算法相比,图像结构相似性约提升了0.02~0.08,图像峰值信噪比约提升了0.2~3.5 dB。