Distributed supervisory control of discrete-event systems with communication delay

This paper identifies a property of delay-robustness in distributed supervisory control of discrete-event systems (DES) with communication delays. In previous work a distributed supervisory control problem has been investigated on the assumption that inter-agent communications take place with negligible delay. From an applications viewpoint it is desirable to relax this constraint and identify communicating distributed controllers which are delay-robust, namely logically equivalent to their delay-free counterparts. For this we introduce inter-agent channels modeled as 2-state automata, compute the overall system behavior, and present an effective computational test for delay-robustness. From the test it typically results that the given delay-free distributed control is delay-robust with respect to certain communicated events, but not for all, thus distinguishing events which are not delay-critical from those that are. The approach is illustrated by a workcell model with three communicating agents.     

Theoretical analysis of the slip flow effect on gas-lubricated micro spherical spiral groove bearings for machinery gyroscope

The performance of a gas-lubricated micro spherical spiral groove bearing (MSSGB) with slip flow effect is investigated. A modified Reynolds equation incorporated with Barber’s first-order slip flow model is proposed to investigate the flow characteristics of gas in MSSGBs. Parameter transformation and oblique coordinate transformation are applied to eliminate the curve effect on the calculation domain. An improved finite difference method (FDM) based on Green’s formula is used to solve the Reynolds equation. The perturbation method is adopted to determine the dynamic coefficients. The effects of slip flow and bearing parameters, including the groove depths, rotor speeds, and eccentricity ratios, on the bearing characteristics are investigated and discussed. Prediction results show that the slip flow effect on MSSGB performance is significant. Moreover, the groove depth at micro clearance has a crucial influence on bearing performance.     

Prioritizing agile benefits and limitations in relation to practice usage

In recent years, there has been significant shift from rigid development (RD) toward agile. However, it has also been spotted that agile methodologies are hardly ever followed in their pure form. Hybrid processes as combinations of RD and agile practices emerge. In addition, agile adoption has been reported to result in both benefits and limitations. This exploratory study (a) identifies development models based on RD and agile practice usage by practitioners; (b) identifies agile practice adoption scenarios based on eliciting practice usage over time; (c) prioritizes agile benefits and limitations in relation to (a) and (b). Practitioners provided answers through a questionnaire. The development models are determined using hierarchical cluster analysis. The use of practices over time is captured through an interactive board with practices and time indication sliders. This study uses the extended hierarchical voting analysis framework to investigate benefit and limitation prioritization. Four types of development models and six adoption scenarios have been identified. Overall, 45 practitioners participated in the prioritization study. A common benefit among all models and adoption patterns is knowledge and learning, while high requirements on professional skills were perceived as the main limitation. Furthermore, significant variances in terms of benefits and limitations have been observed between models and adoption patterns. The most significant internal benefit categories from adopting agile are knowledge and learning, employee satisfaction, social skill development, and feedback and confidence. Professional skill-specific demands, scalability, and lack of suitability for specific product domains are the main limitations of agile practice usage. Having a balanced agile process allows to achieve a high number of benefits. With respect to adoption, a big bang transition from RD to agile leads to poor quality in comparison with the alternatives.     

一种融合地理位置信息的协同过滤推荐算法

目前,基于用户消费数据构建的推荐系统在电子商务领域发挥着越来越大的作用,而在这些数据中,商家本身具有的地理位置信息忠实地记录了用户的消费痕迹,能够有效反映出用户在地理位置维度上的个人偏好信息,从而对推荐系统具有非常重要的意义。现有工作一般只利用了用户对地点的评价以及地点之间的距离,无法反映出不同地点之间的关联关系,以及用户在不同地点中的偏好权重问题。该文从地理区域划分的角度出发,研究了用户在区域范围内的消费兴趣偏好,以及不同粒度级别的区域划分方法对推荐模型的影响,探索了在推荐过程中有效融合地域信息的方法,考虑了包括地区的全局性影响、用户对地区的偏好等,结合这些因素提出了融合地理位置信息的推荐模型LGE、LGN及LRSVD。通过在Yelp数据集上的实验表明,这些模型相比于传统的推荐算法能够有效提高预测效果。     

Improved Adaptive Controller Synthesis of Piecewise‐Affine Systems

This paper considers the adaptive control problem for piecewise affine systems (PWS), a novel synthesis framework is presented based on the piecewise quadratic Lyapunov function (PQLF) instead of the common quadratic Lyapunov function to achieve the less conservatism. First, by designing the projection‐type piecewise adaptive law, the problem of the adaptive control of PWS can be reduced to the control problem of augmented piecewise systems. Then, we construct the piecewise affine control law for augmented piecewise systems in such a way that the PQLF can be employed to establish the stability and performance. In particular, the Reciprocal Projection Lemma is employed to formulate the synthesis condition as linear matrix inequalities (LMIs), which enables the proposed PQLF approach to be numerically solvable. Finally, an engineering example is shown to illustrate the synthesis results.     

Iterative learning control for two-dimensional linear discrete systems with Fornasini-Marchesini model

International Journal of Control, Automation and Systems - Almost all existing iterative learning control (ILC) algorithms have focused on one-dimensional (1-D) dynamical systems, and seldom were...     

基于MongoDB的轨迹大数据时空索引构建方法

近年来,随着计算机技术与无线传感器网络的发展,轨迹大数据越来越得到人们的关注.针对海量轨迹数据在存储与查询中出现的效率问题,文章基于文档型非关系型数据库MongoDB提出了一套基于四叉树的道路网时空索引,实现海量轨迹数据的高效查询.通过对太原市1915辆出租车的50万条轨迹数据进行时空查询,在不同数据量与不同并发数下测试道路网时空索引与MongoDB复合时空索引的效率表现.实验结果显示道路网时空索引在数据量大于10万时有较好表现,并能够适应不同并发数下的时空查询,验证了道路网时空索引构建方法的可行性和高效性.     

基于桥系数的分裂社区检测算法研究

研究社区结构有助于揭示网络结构和功能之间的关系,而社区检测是社区结构研究的基础和核心。该文定义了一种聚集度桥系数,将其应用到社区检测中,设计出一种分裂社区检测方法,包括分裂和合并两个算法。分裂算法使用桥系数识别社区间边,通过迭代删除社区间边分解网络,从而发现网络中的社区结构;合并算法根据社区连接强度合并社区,可以揭示社区结构中的分层嵌套的现象。在六个社会网络数据集上的实验表明,本文算法可以有效的将网络分裂为有意义的社区,并且准确性接近或超过经典的社区检测算法。     

A new generator of causal ideal internal dynamics for a class of unstable linear differential equations

The generator design for causal ideal internal dynamics (IID), namely, solving IID, is a fundamental problem in a nonminimum‐phase output tracking process. In this paper, for a class of unstable matrix differential equations, a new causal IID generator is proposed, whose parameters are partly chosen via optimization. Compared with existing similar design schemes, it is applicable to matrix differential equations with singular system matrices. Also, it requires less computation, avoids taking higher order derivatives, and can be easily extended to treat slowly time‐varying matrix differential equations without the need for extra computation. Copyright © 2016 John Wiley & Sons, Ltd.