Human Cyber Physical Systems(HCPSs)in the Context of New-Generation Intelligent Manufacturing

An intelligent manufacturing system is a composite intelligent system comprising humans,cyber systems,and physical systems with the aim of achieving specific manufacturing goals at an optimized level.This kind of intelligent system is called a human-cyber-physical system(HCPS).In terms of technology,HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing.It can be concluded that the essence of intelligent manufacturing is to design,construct,and apply HCPSs in various cases and at different levels.With advances in information technology,intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing,and is evolving toward new-generation intelligent manufacturing(NGIM).NGIM is characterized by the in-depth integration of new-generation artificial intelligence(AI)technology(i.e.,enabling technology)with advanced manufacturing technology(i.e.,root technology);it is the core driving force of the new industrial revolution.In this study,the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs,and the implications,characteristics,technical frame,and key technologies of HCPSs for NGIM are then discussed in depth.Finally,an outlook of the major challenges of HCPSs for NGIM is proposed.

Chaotic Sandpiper Optimization Based Virtual Machine Scheduling for Cyber-Physical Systems

Recently,with the growth of cyber physical systems(CPS),several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively.Besides,the cloud computing(CC)enabled CPS offers huge processing and storage resources for CPS thatfinds helpful for a range of application areas.At the same time,with the massive development of applica-tions that exist in the CPS environment,the energy utilization of the cloud enabled CPS has gained significant interest.For improving the energy effective-ness of the CC platform,virtualization technologies have been employed for resource management and the applications are executed via virtual machines(VMs).Since effective scheduling of resources acts as an important role in the design of cloud enabled CPS,this paper focuses on the design of chaotic sandpi-per optimization based VM scheduling(CSPO-VMS)technique for energy effi-cient CPS.The CSPO-VMS technique is utilized for searching for the optimum VM migration solution and it helps to choose an effective scheduling strategy.The CSPO algorithm integrates the concepts of traditional SPO algorithm with the chaos theory,which substitutes the main parameter and combines it with the chaos.In order to improve the process of determining the global optimum solutions and convergence rate of the SPO algorithm,the chaotic concept is included in the SPO algorithm.The CSPO-VMS technique also derives afitness function to choose optimal scheduling strategy in the CPS environment.In order to demonstrate the enhanced performance of the CSPO-VMS technique,a wide range of simulations were carried out and the results are examined under varying aspects.The simulation results ensured the improved performance of the CSPO-VMS technique over the recent methods interms of different measures.

Intelligent Smart Grid Stability Predictive Model for Cyber-Physical Energy Systems

A cyber physical energy system(CPES)involves a combination of pro-cessing,network,and physical processes.The smart grid plays a vital role in the CPES model where information technology(IT)can be related to the physical system.At the same time,the machine learning(ML)modelsfind useful for the smart grids integrated into the CPES for effective decision making.Also,the smart grids using ML and deep learning(DL)models are anticipated to lessen the requirement of placing many power plants for electricity utilization.In this aspect,this study designs optimal multi-head attention based bidirectional long short term memory(OMHA-MBLSTM)technique for smart grid stability predic-tion in CPES.The proposed OMHA-MBLSTM technique involves three subpro-cesses such as pre-processing,prediction,and hyperparameter optimization.The OMHA-MBLSTM technique employs min-max normalization as a pre-proces-sing step.Besides,the MBLSTM model is applied for the prediction of stability level of the smart grids in CPES.At the same time,the moth swarm algorithm(MHA)is utilized for optimally modifying the hyperparameters involved in the MBLSTM model.To ensure the enhanced outcomes of the OMHA-MBLSTM technique,a series of simulations were carried out and the results are inspected under several aspects.The experimental results pointed out the better outcomes of the OMHA-MBLSTM technique over the recent models.

信息物理系统(cyber physical systems)及其对网络科学研究的影响

信息物理系统(cyber physical systems,简称CPS)是集成计算、通信与控制于一体的下一代智能系统。该系统由于存在巨大的应用前景而日益收到人们的关注。本文对介绍了CPS的特点,并对CPS面临的机遇和挑战进行了探讨,最后指出了CPS对复杂网络研究的影响。

Digital Twins and Cyber Physical Systems toward Smart Manufacturing and Industry 4.0:Correlation and Comparison

State-of-the-art technologies such as the Internet of Things(IoT),cloud computing(CC),big data analytics(BDA),and artificial intelligence(AI)have greatly stimulated the development of smart manufacturing.An important prerequisite for smart manufacturing is cyber-physical integration,which is increasingly being embraced by manufacturers.As the preferred means of such integration,cyber-physical systems(CPS)and digital twins(DTs)have gained extensive attention from researchers and practitioners in industry.With feedback loops in which physical processes affect cyber parts and vice versa,CPS and DTs can endow manufacturing systems with greater efficiency,resilience,and intelligence.CPS and DTs share the same essential concepts of an intensive cyber-physical connection,real-time interaction,organization integration,and in-depth collaboration.However,CPS and DTs are not identical from many perspectives,including their origin,development,engineering practices,cyber-physical mapping,and core elements.In order to highlight the differences and correlation between them,this paper reviews and analyzes CPS and DTs from multiple perspectives.

空中交通CPS结构特性及韧性评估

针对空中交通体系结构复杂、耦合性强、脆弱性高的特点,为缓解因受扰导致的级联失效现象,对其结构韧性进行研究。建立了空中交通信息物理系统(CPS)模型,提出同层度与层间度、同层介数与层间介数等指标,分析级联失效过程;提出空中交通CPS韧性的概念,并采用定量评估方法对受损能力和恢复能力进行度量;对比不同扰动-恢复策略下的空中交通CPS表现,制定最佳恢复策略,提高受扰时的韧性。以华东地区空中交通CPS为例进行分析,结果表明:空中交通CPS网络度分布服从幂率分布,介数服从指数分布;在基于介数度值扰动下,采用介数恢复策略可以有效提高受扰时空中交通CPS的韧性。

基于CPS的单交叉口信号滚动优化控制模型

为了采用现代信息技术提升单交叉口的通行效率,综合考虑信息物理系统(CPS)的特性和功能,构建了基于CPS的单交叉口信号滚动优化控制架构;提出了交叉口信号优化控制的分层建模思路与框架,实现了对交叉口不同层级的状态描述;针对不同流量环境,分别以单位时间车均预计延误和加权排队长度比作为优化目标,进行实时信号优化,构建了基于CPS的分层滚动优化模型;搭建了基于SUMO与Python的实时交互仿真环境,针对未饱和、过饱和以及饱和状态变化3种流量场景进行案例分析.算例结果表明,与Transyt、Synchro、Webster、感应控制、承载力方法相比,所提模型均取得了更优的控制效果,车均延误和平均排队长度最多分别可减少43.75%和16.05%,溢流时间最多可延长37.93%.

A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over Internet.It plays a key role in modern industry since it connects physical and cyber worlds.In order to meet ever-changing industrial requirements,its structures and functions are constantly improved.Meanwhile,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and practitioners.This paper presents a survey of state-of-the-art results of cyber attacks on cyber physical systems.First,as typical system models are employed to study these systems,time-driven and event-driven systems are reviewed.Then,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are discussed.In particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and defenders.Namely,both attack and defense strategies are discussed based on different system models.Some challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems

Cyber physical systems（CPS） recently emerge as a new technology which can provide promising approaches to demand side management（DSM）, an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufac^ring center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

A quantitative analysis model of grid cyber physical systems

Conventional power systems are being developed into grid cyber physical systems(GCPS) with widespread application of communication, computer, and control technologies. In this article, we propose a quantitative analysis method for a GCPS. Based on this, we discuss the relationship between cyberspace and physical space, especially the computational similarity within the GCPS both in undirected and directed bipartite networks. We then propose a model for evaluating the fusion of the three most important factors: information, communication, and security. We then present the concept of the fusion evaluation cubic for the GCPS quantitative analysis model. Through these models, we can determine whether a more realistic state of the GCPS can be found by enhancing the fusion between cyberspace and physical space. Finally, we conclude that the degree of fusion between the two spaces is very important, not only considering the performance of the whole business process, but also considering security.

Simulation of Cyber-Physical Systems of Systems： Some Research Areas-Computational Understanding, Awareness, and Wisdom

After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.

A cyberphysical-based approach to leader-following consensus for distributed multi-agent systems

This paper considers a leader-following consensus problem for first-order linear multi-agent systems with constant input and communication time-delays. Based on the idea of cyber physical systems, the use of control states of neighboring agents, a new distributed control protocol is presented. Furthermore, in terms of linear matrix inequalities, sufficient conditions of leader-following consensus for multi-agent systems with constant input, communication and input time-delays are presented respectively. Numerical simulations on multi-agent systems are presented to demonstrate the efficiency of the proposed criteria.

Energy Aware Secure Cyber-Physical Systems with Clustered Wireless Sensor Networks

Recently,cyber physical system(CPS)has gained significant attention which mainly depends upon an effective collaboration with computation and physical components.The greatly interrelated and united characteristics of CPS resulting in the development of cyber physical energy systems(CPES).At the same time,the rising ubiquity of wireless sensor networks(WSN)in several application areas makes it a vital part of the design of CPES.Since security and energy efficiency are the major challenging issues in CPES,this study offers an energy aware secure cyber physical systems with clustered wireless sensor networks using metaheuristic algorithms(EASCPSMA).The presented EASCPS-MA technique intends to attain lower energy utilization via clustering and security using intrusion detection.The EASCPSMA technique encompasses two main stages namely improved fruit fly optimization algorithm(IFFOA)based clustering and optimal deep stacked autoencoder(OSAE)based intrusion detection.Besides,the optimal selection of stacked autoencoder(SAE)parameters takes place using root mean square propagation(RMSProp)model.The extensive performance validation of the EASCPS-MA technique takes place and the results are inspected under varying aspects.The simulation results reported the improved effectiveness of the EASCPS-MA technique over other recent approaches interms of several measures.

信息物理系统(cyber-physical system)时空建模方法及在温室控制中的应用

传统农业采用人工方式对温室进行控制,但是随着现代农业的快速发展,这种人工投入大、精度低的控制方式已不能满足现代农业需要。该文基于分层有限状态机和事件晶格的概念,建立3层的信息物理系统模型,并提出一种基于分层有限状态机的信息物理系统时空建模方法,同时利用该建模方法开发了新的温室控制系统。该系统能够将物理层传感器感知到的温室物理环境数据通过物理-信息层汇聚节点融合后上报信息层决策节点得到决策信息,物理-信息层控制节点分析决策信息得到控制信息后下传物理层执行器进行控制。由于该系统模型考虑了各层状态机中事件的时空属性,能够将温室控制的正确率由传统基于物联网的温室控制方法的80.20%提高到87.20%,错误肯定率和错误否定率由7.50%和12.30%下降到3.60%和9.20%,保障温室环境满足作物生长对温度、湿度和光照的要求。

Topology-Based and Event-Oriented Approach to Simulation of Cyber-Physical Systems

A simulation model for cyber-physical systems(CPSs)was presented.The model was developed by the method of combination of topology-based and event-oriented that could be used to simulate systems with routing flexibility,service-selection flexibility and service- mode flexibility overall by integrating the strategies related.The validity of the model has been verified by two extensive experiments.

Security and Privacy Challenges in Cyber-Physical Systems

Cyber-Physical Systems, or Smart-Embedded Systems, are co-engineered for the integration of physical, computational and networking resources. These resources are used to develop an efficient base for enhancing the quality of services in all areas of life and achieving a classier lifestyle in terms of a required service’s functionality and timing. Cyber-Physical Systems (CPSs) complement the need to have smart products (e.g., homes, hospitals, airports, cities). In other words, regulate the three kinds of resources available: physical, computational, and networking. This regulation supports communication and interaction between the human word and digital word to find the required intelligence in all scopes of life, including Telecommunication, Power Generation and Distribution, and Manufacturing. Data Security is among the most important issues to be considered in recent technologies. Because Cyber-Physical Systems consist of interacting complex components and middle-ware, they face real challenges in being secure against cyber-attacks while functioning efficiently and without affecting or degrading their performance. This study gives a detailed description of CPSs, their challenges (including cyber-security attacks), characteristics, and related technologies. We also focus on the tradeoff between security and performance in CPS, and we present the most common Side Channel Attacks on the implementations of cryptographic algorithms (symmetric: AES and asymmetric: RSA) with the countermeasures against these attacks.

Transportation-cyber-physical-systems-oriented engine cylinder pressure estimation using high gain observer

In transportation cyber-physical-systems （T-CPS）, vehicle-to-vehicle （V2V） communications play an important role in the coordination between individual vehicles as well as between vehicles and the roadside infrastructures, and engine cylinder pressure is significant for engine diagnosis on-line and torque control within the information exchange process under V2V communications. However, the parametric uncertainties caused from measurement noise in T-CPS lead to the dynamic performance deterioration of the engine cylinder pressure estimation. Considering the high accuracy requirement under V2V communications, a high gain observer based on the engine dynamic model is designed to improve the accuracy of pressure estimation. Then, the analyses about convergence, converge speed and stability of the corresponding error model are conducted using the Laplace and Lyapunov method. Finally, results from combination of Simulink with GT- Power based numerical experiments and comparisons demonstrate the effectiveness of the proposed approach with respect to robustness and accuracy.

From Mechatronic Components to Industrial Automation Things: An IoT Model for Cyber-Physical Manufacturing Systems

IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, which we call IoT wrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modelling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.

基于CPSS视角的需求响应能力评估综述

对信息—物理—社会系统与需求响应评估的结合进行综述。首先对信息物理系统的历史和框架进行分析。接着总结了现有的需求响应研究现状,包括需求响应潜力评估的意义、分类和评估方法。对于需求响应能力评估的数据来源进行总结,包括问卷调查和运行数据采集。在信息—物理—社会系统与需求响应结合方面,分别分析需求响应的物理域、信息域和社会域基础,介绍相应的建模方法和研究内容。最后,对未来的研究展望进行讨论,包括市场考核机制、快速仿真与建模技术以及综合能源下的需求响应管理。

一种使用STL逻辑监控CPS的可解释规范挖掘方法

随着信息物理融合系统(CPS)日益复杂,很难捕获其相关行为并以一种可解释的方式检测它.因此本文提出了一种基于线性支持向量机(LSVM)框架的规范挖掘算法,从有限长度的信号轨迹中挖掘具有可解释性的信号时序逻辑(STL)公式.挖掘出的STL公式可以作为监控行为的抽象,用于CPS运行时验证的监控机制中.该算法根据一组被标记的有限时间轨迹和STL模板公式,将信号时序逻辑特有的鲁棒性满意度与LSVM的优化算法相结合生成所需规范.另外,本文还将对一维信号轨迹的规范挖掘技术扩展到多维信号上.最后,通过两个案例研究来说明提出算法的可行性和优势,结果表明该算法在保证高准确率的前提下,执行效率和可解释性都优于其他的规范挖掘算法.