Intelligent Information‐Centric Networking routing scheme under imprecise information

Information‐Centric Networking (ICN) has been accepted to overcome some weaknesses of the current Internet architecture, showing that “what is being exchanged” is more important than “who are exchanging information.” Given the inadequate considerations on Quality of Service (QoS) and energy saving in ICN routing, we propose in this paper a routing algorithm to enhance the two aspects. At first, on one hand, Cauchy distribution is used as a fuzzy model to evaluate users' QoS requirements, such as bandwidth, delay, and error rate; on the other hand, we formulate energy saving problem to evaluate the green quality of routing algorithm. Then, we design a link selection approach by considering QoS and energy saving, which belongs to a multi‐objective decision problem resolved by intelligent drops algorithm. Finally, we implement the proposed algorithm and compare it with the famous adaptive forwarding mechanism in terms of some significant metrics, and the experimental results reveal that the proposed algorithm is more efficient.     

基于蛛状网拓扑智能变电站“三层一网”通信系统研究

在110kV及以下电压等级变电站中，“三层一网”架构虽然简化了二次系统接线，但实时性和可靠性难以保证。针对传统拓扑结构下的实时性和可靠性无法同时达到最优效果的问题，本文采用“三层一网”架构下蛛状网拓扑结构，仿真结果表明该结构下的通信系统实时性最佳，解决了传统拓扑结构实时性差的问题，并结合算例验证了其可行性；运用故障树分析法定量分析不同结构的可靠性，结果表明蛛状网结构的可靠性更好。为解决研究复杂的通信系统可靠性时传统故障树方法有一定的局限性的问题，本文引入T-S模糊故障理论，建立T-S故障树模型，计算结果表明蛛状网结构下通信系统可靠性最好。根据本文研究可以得到蛛状网拓扑结构能同时提高通信系统实时性和可靠性的结论。     

Disturbance observer-based adaptive boundary iterative learning control for a rigid-flexible manipulator with input backlash and endpoint constraint

In this article, an observer-based adaptive boundary iterative learning control law is developed for a class of two-link rigid-flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the adaptive boundary control design. A barrier Lyapunov function is incorporated with boundary control law to restrict the endpoint state. Based on the defined barrier composite energy function, the tracking angle error convergence of the rigid part is guaranteed, and the vibrations of the flexible part are suppressed through the rigorous analysis. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed control.     

商用车输入轴生产线智能化建设

根据用户要求,从空间布局和网络拓扑方面介绍了输入轴智能化生产线的建设过程,详述各环节的工作任务和动作机能,给出了主要零/部件的结构图样。生产线投用后,成效显著。对智能化制造商具有指导意义,对商用车用户具有借鉴意义。     

能源互联网智能感知技术框架与应用布局

智能感知技术是数字化的关键技术之一,是能源互联网的基础技术。在当前数字化进程深入推动能源革命的背景下,智能感知技术已成为能源互联网建设与发展的数字引擎。文章总结了能源互联网框架下智能感知技术的战略背景、业务需求及重要意义,通过分析当前存在的问题,详细阐述了智能感知技术理论及发展趋势,梳理智能感知核心技术框架,提出系统性技术标准体系,并给出了能源互联网“源-网-荷-储”智能感知应用布局,最后结合我国能源互联网发展现状,对智能感知建设路径与发展方向进行了探讨与展望。     

浅析智能网联汽车感知系统电磁兼容性

本文将就智能网联汽车感知系统中的电子兼容技术进行深入的分析和探究。     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

基于LoRa物联网技术的智能照明控制方案在高速公路上的应用——以北京新机场高速公路(南五环-北京新机场)为例

文章结合北京新机场高速公路照明工程实例,阐述了常规照明控制系统的现状,分析了基于新兴的LoRa物联网技术智能照明控制方案的系统原理和系统构成、系统在高速公路智能照明控制领域的应用以及系统应用能达到的节能和管理效益的提升效果,并对系统的扩展应用前景做了研究分析。     

Intelligent scheduling of discrete automated production line via deep reinforcement learning

The reinforcement learning (RL) is being used for scheduling to improve the adaptability and flexibility of an automated production line. However, the existing methods only consider processing time certain and known and ignore production line layouts and transfer unit, such as robots. This paper introduces deep RL to schedule an automated production line, avoiding manually extracted features and overcoming the lack of structured data sets. Firstly, we present a state modelling method in discrete automated production lines, which is suitable for linear, parallel and re-entrant production lines of multiple processing units. Secondly, we propose an intelligent scheduling algorithm based on deep RL for scheduling automated production lines. The algorithm establishes a discrete-event simulation environment for deep RL, solving the confliction of advancing transferring time and the most recent event time. Finally, we apply the intelligent scheduling algorithm into scheduling linear, parallel and re-entrant automated production lines. The experiment shows that our scheduling strategy can achieve competitive performance to the heuristic scheduling methods and maintains stable convergence and robustness under processing time randomness.     

基于物联网的智慧林业可持续发展策略研究

随着我国科技的不断进步,在“互联网+”大数据的背景下,林业的智慧化发展是必经之路。虽然我国智慧林业的发展已经取得了一定的突破,但是仍然存在着许多问题。基于此,文章在物联网技术的基础上,对智慧林业的可持续发展策略进行探讨。