General Floorplans with L/T-Shaped Blocks Using Corner Block List

With the recent advent of deep submicron technology and new packing schemes, the components in the integrated circuit are often not rectangular. On the basis of the representation of Corner Block List （CBL）, we propose a new method of handling rectilinear blocks. In this paper, the handling of the rectilinear blocks is simplified by transforming the L/T- shaped block problem into the Mign-abutment constraint problem. We devise the block rejoining process and block alignment operation for forming the L/T-shaped blocks into their original configurations. The shape flexibility of the soft blocks, and the rotation and reflection of L/T-shaped blocks are exploited to obtain a tight packing. The empty rooms are introduced to the process of block rejoining. The efficiency and effectiveness of the proposed method are demonstrated by the experimental results on a set of some benchmark examples.     

结构约束和样本稀疏表示的图像修复

本文探讨了一种利用结构约束和样本稀疏表示,对结构信息缺损较大时的图像修复方法。利用多项式曲线拟合方式修复图像边缘信息,约束结构的修复;采用样本稀疏表示的窄带模型,优先修复结构信息;利用平移块的稀疏表示方法修复纹理信息。仿真实验结果表明,该方法修复图像质量高,既可较好地修复图像的边缘结构,又能保持结构的整体平滑性。     

加温退火算法及其在旅行商问题中的应用

传统的模拟退火算法初始温度人工选取可能出现过高或过低,致使运行时间长、搜索效率低。在传统的模拟退火算法中引入加温过程,可以根据算法自身的运行得到合适的初始温度与较好的解质。文章将加温前后的模拟退火算法应用于旅行商问题,验证了加温模拟退火算法的高效性。     

一种改进的多目标混合遗传算法及应用

在NSGA-II算法中引入自适应交叉算子和自适应变异算子,将模拟退火算法与改进的NSGA-II算法相结合,并应用到武器装备供应合同商的选择与评价中。实验结果表明,非劣解在目标空间分布均匀,算法收敛性好,为求解武器装备供应合同商选择的多目标问题提供了一种有效的工具。     

径向基函数混沌神经元系统及其应用

建立了径向基函数混沌神经网络模型以及径向基函数混沌神经元模型,分析其产生混沌后收敛的原因,通过撤销模拟退火策略使过程无法收敛,从而构建出永久保持混沌状态的混沌神经元动力系统,分析了该系统的时间序列指标,证明其永久保持混沌状态的可行性;将该系统应用于灰度图像的加密解密,阐述了其原理及算法;分析了该算法的抗穷举能力,考察了原图像与加密图像的直方图,由此说明了该算法的抗统计分析的能力。     

改进十字链表的存储方法在短路电流计算中的应用

节点导纳矩阵是一个稀疏矩阵,短路电流计算需要对导纳矩阵数据进行查询。为了既能保持快速按行列查询元素数值,又进一步提高按数值查询其所在行列的效率,以便于存储调用及后续矩阵的处理,提出构建高度平衡二叉树的改进十字链表方法,即在十字链表存储的基础上,拓展存储数据结点指针域,形成平衡二叉树,将高度维持在(O(log2n)),平均查找长度也可维持在(O(log2n)),大大降低操作时间复杂度,提高数值查询效率。同时,为保证测试结果的公平性,把构建高度平衡二叉树的时间计入总时间,以进行对比。通过相应算例,验证了该改进方法的高效性。     

自适应状态转移模拟退火算法及其应用

状态转移模拟退火算法(STASA)作为解决复杂优化问题的有效方法,其搜索效率依赖于搜索算子和参数值的选择,在一些高维复杂问题上出现效率低下的问题。提出一种自适应状态转移模拟退火算法(ASTSA),通过自适应算子和参数选择策略来提高算法的适用性和求解效率;借鉴群智能算法的均值更新方法对平移算子进行改进,增强算子的搜索特性。通过23个基准测试函数和8个工程设计问题进行实验验证并与其他算法对比,证明了ASTSA算法和改进策略的有效性。     

基于模拟退火选择的动态免疫算法及其应用

借鉴人工免疫系统的记忆、动态识别等功能及模拟退火选择理论,提出一种适用于求解动态环境优化问题的动态免疫算法(DIASA),并将其用于高维动态约束背包问题。算法设计包括:(1)抗体的亲和力随群体进化而变化;(2)可行抗体被克隆和动态突变,突变概率与抗体浓度相关,而非可行抗体按价值密度贪婪修正;(3)新环境初始群经环境识别算子按不同方式生成,相似环境初始群由记忆细胞及随机抗体产生。数值实验中,选取著名的动态进化算法(ETGA)和动态免疫遗传算法(ISGA),通过不同难度的高维动态约束背包问题进行仿真比较,结果表明:DIASA较算法ISGA和ETGA对不同问题在各环境内表现较强的优化性能,群体中抗体多样性保持较好,能快速跟踪不同环境的最优值,收敛性强。     

Hybrid flexible flowshops with sequence-dependent setup times and machine availability constraints

One of the common assumptions in the field of scheduling is that machines are always available in the planning horizon. This may not be true in realistic problems since machines might be busy processing some jobs left from previous production horizon, breakdowns or preventive maintenance activities. Another common assumption is the consideration of setup times as a part of processing times, while in some industries, such as printed circuit board and automobile manufacturing, not only setups are an important factor but also setup magnitude of a job depends on its immediately preceding job on the same machine, known as sequence-dependent setup times. In this paper, we consider hybrid flexible flowshops with sequence-dependent setup times and machine availability constraints caused by preventive maintenance. The optimization criterion is the minimization of makespan. Since this problem is NP-hard in the strong sense, we propose three heuristics, based on SPT, LPT and Johnson rule and two metaheuristics based on genetic algorithm and simulated annealing. Computational experiments are performed to evaluate the efficiencies of the algorithms.     

模糊控制器优化方法及其在传感器补偿中的应用

为了减小压力传感器温度漂移造成的测量误差,使用0阶T—S模糊控制器对压力传感器温度附加误差进行校正,校正后的误差为±0.3%,且零位温度系数和灵敏度温度系数都降低1个数量级以上。使用模拟退火算法对模糊规则进行寻优,提高了校正精度,并保持了0阶T—S模糊控制器运算简单和速度快的特点,使之能快速地完成传感器的温度补偿。     

Regulator problem for linear systems with constraints on control and its increment or rate

This paper discusses the problem of constraints on both control and its rate or increment, for linear systems in state space form, in both the continuous and discrete-time domains. Necessary and sufficient conditions are derived for autonomous linear systems with constrained state increment or rate (for the continuous-time case), such that the system evolves respecting incremental or rate constraints. A pole assignment technique is then used to solve the inverse problem, giving stabilizing state feedback controllers that respect non-symmetrical constraints on both control and its increment or rate. An illustrative example shows the application of the method on the double integrator problem.     

稀疏限制的增量式鲁棒非负矩阵分解及其应用

针对鲁棒非负矩阵分解（RNMF）的运算规模随训练样本数量逐渐增多而不断增大的问题，提出一种稀疏限制的增量式鲁棒非负矩阵分解算法。首先，对初始数据进行鲁棒非负矩阵分解；然后，将其分解结果参与到后续迭代运算；最后，在对系数矩阵增加稀疏限制的情况下与增量式学习相结合，使目标函数值在迭代求解时下降地更快。该算法在节省运算时间的同时提高了分解后数据的稀疏度。在数值实验中，将所提算法与鲁棒非负矩阵分解算法、稀疏限制的鲁棒非负矩阵分解（RNMFSC）算法进行了比较。在ORL和YALE人脸数据库上的实验结果表明，所提算法在运算时间和分解后数据的稀疏度等方面均优于其他两个算法，并且还具有较好的聚类效果，尤其在YALE人脸数据库上当聚类类别数为3时该算法的聚类准确率达到了91.67%。     

双三次NURBS曲面矩阵块表示及在曲面设计中的应用

研究了NURBS三次与二次曲面的矩阵块表示及在曲面设计中的应用。给出了NURBS三次与二次基函数系数矩阵表示和NURBS三次曲面矩阵块表示。从矩阵块表示中可很清楚地看出参数区间、曲面片与控制顶点对应关系,这点对NURBS曲面自由变形与求解都很重要。通过在Java2．0与Java3D环境下检验证明该算法高效可靠。     

考虑量化和通信受限的有限时间确定学习控制及其应用

本文针对一类含有量化输入和外部扰动的严格反馈非线性系统,提出了一种考虑量化和通信受限的有限时间确定学习控制方法.该方法包含离线学习训练和在线触发控制两个阶段.首先,在离线学习训练阶段采用神经网络对系统中的未知非线性函数进行逼近,引入指令滤波反步技术克服“计算爆炸”的问题,并在控制过程中实现系统未知动态的知识获取和存储.随后,利用所获取的经验知识,设计了基于确定学习机制的在线触发控制器.应用李雅普诺夫稳定性理论证明了闭环系统实际有限时间稳定,跟踪误差在有限时间内收敛到原点的邻域内,并能够排除采样中的芝诺现象.最后,通过飞行器仿真验证了所提方案的有效性.     

Asymptotic harmonic generator and its application to finite time orbital stabilization of a friction pendulum with experimental verification

A second order sliding mode approach to orbital stabilization is presented and tested on a friction pendulum, operating under uncertain conditions. The quasihomogeneous control synthesis is utilized to design a variable structure controller that drives the pendulum to a model orbit in finite time in spite of the presence of external disturbances with an a priori known magnitude bound. A well-known Van der Pol oscillator is modified to be introduced into the synthesis as a reference model. This modification is made to shape the oscillator limit cycle to a harmonic one, thereby yielding an asymptotic harmonic generator of the periodic motion. The parameters of the asymptotic harmonic generator are shown to specify amplitude and frequency of the limit cycle production and damping of non-linear oscillations of the generator. The resulting closed-loop system is capable of moving from one orbit to another by changing these parameters dynamically. Performance issues of the controller constructed are illustrated in an experimental study.     

嵌段共聚物球形胶束体系的标度理论及其与均匀场理论的对比研究

本文建立了用于嵌段共聚物胶束体系定量计算的标度理论模型,讨论了标度理论与均匀场模型的差异。在极性和非极性溶剂体系中,定量考察了平衡态胶束聚集数、胶束过渡区聚合物浓度分布、胶束半径和内界面处的聚合物浓度等平衡性质,以及嵌段共聚物嵌段比例、摩尔质量等因素对上述性质的影响。与实验及均匀场模型的对比结果硅示,均匀场模型的拟均相假设对胶束聚集数等平衡性质的计算不会产生显著偏差,标度理论模型与均匀场模型都能够较好地描述胶束体系,两模型也获得了较好的一致。此外,标度理论模型能够给出胶束内的浓度分布。即使在高聚集数的情况下,胶束内界面处溶剂的含量仍然很高（〉50％）,这表明有必要对内界面张力的计算进行修正,而均匀场模型则忽略了此项修正。     

Decentralised model predictive control with stability constraints and its application in process control

This paper presents a novel decentralised model predictive control for a plant consisting of interconnected systems. A constructive technique for online stabilisation that is applicable to the model predictive controllers (MPC) is developed. The plant-wise stability is achievable by the newly introduced asymptotically positive realness constraint (APRC) for MPC. Simulations are provided to demonstrate the efficiency of the presented APRC.     

有卸货顺序约束的集装箱装载问题及算法研究

对有卸货顺序约束的三维集装箱问题进行了描述.基于禁忌规则,采用了求解该问题的模拟退火算法,设计了货物的摆放规则和序列生成方式.采用3种邻域,根据邻域的不同,构造了2种禁忌表.根据问题的特点,在模拟退火算法抽样过程中加入了禁忌规则.介绍了算法的原理,给出了具有代表性算例试验结果并且进行了分析.试验结果表明,提出的混合算法对有卸货顺序约束的集装箱三维装载问题的有效性.     

Region with velocity constraints: map information and its usage for safe motion planning of a mobile robot in a public environment

Recently, various autonomous mobile robots have been developed for practical use. To support the coexistence of robots and humans in real environments, we propose a concept named ‘Region with Velocity Constraints (RVC),’ which is set around hazardous areas. RVCs are regions where the velocities of the robot are constrained to predefined values. Inside the RVCs, the robot has to reduce its translational velocity to avoid predicted hazards such as collisions with obstacles, and to reduce its rotational velocity to prevent undesirable motions such as sharp turns. We also propose a motion planning method for navigating the mobile robot in an environment with RVCs based on the Navigation Function and Global Dynamic Window Approach. Our method generates a trajectory satisfying both translational and rotational velocity constraints to be compatible with the surroundings. Moreover, to demonstrate the validity of our method, we performed numerical simulations and experiments.     

Parameter identification and application of a distributed parameter coupled system with a movable inner boundary

In this paper, we establish a distributed parameter coupled system concerning Arctic sea ice temperature field, in which the ice thickness is regarded as a movable inner boundary of the space domain. The existence and continuity of the weak solution to the coupled system are proved. According to the measured data, we establish a parameter identification model with the ice thickness as control variable and the coupled system as constraints. Finally, an optimization algorithm is constructed on the basis of non-overlapping domain decomposition method and semi-implicit difference scheme. Through numerical calculation, we obtain the characteristics of the ice thicknesses and the ice temperatures.