In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the...In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.展开更多
Traditional design,manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost inefective manner.A unifed platform for efcient and intelligent...Traditional design,manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost inefective manner.A unifed platform for efcient and intelligent designmanufacturing-maintenance of mechanical equipment and systems is highly needed in this rapidly digitized world.In this work,the defnition of digital twin and its research progress and associated challenges in the design,manufacturing and maintenance of engineering components and equipment were thoroughly reviewed.It is indicated that digital twin concept and associated technology provide a feasible solution for the integration of design-manufacturingmaintenance as it has behaved in the entire lifecycle of products.For this aim,a framework for information-physical combination,in which a more accurate design,a defect-free manufacturing,a more intelligent maintenance,and a more advanced sensing technology,is prospected.展开更多
With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies ...With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.展开更多
As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There hav...As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.展开更多
This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the con...This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.展开更多
With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and powe...With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution systems.Supporting these applications,an important family of methods are based on graphs.For DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of systems.To this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex Systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex systems.The established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision supports.Besides,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the KG.With the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple systems.The bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.展开更多
Systems engineering practices are evolving to address fast-changing needs in fielding complex systems.These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by hu...Systems engineering practices are evolving to address fast-changing needs in fielding complex systems.These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by humans’natural capabilities.We propose that systems engineering must aid systems engineering managers by providing architectural alternatives and design options.Further,as systems become more complex and dynamic,there is an increased need to identify hidden risks,model emergent behav-ior,and expose hidden patterns in the behavior of stakeholders.Systems engineering needs to evolve to build fast-fielded,resilient,and adaptive systems that leverage posi-tive reinforcement feedback loops with multiple experimental and real-world information sources.The very basis of systems engineering must evolve from today’s development paradigms to a future that leverages modeling,simulation,and artificial intelligence to drastically improve the capability and agility for developing new systems.This paper proposes a common way forward to enable this new form of complex adaptive systems engineering.展开更多
With the development of information and communication technology and the advent of the Internet of Things(IoT)era,cyber-physical system(CPS)is becoming the trend of products or systems.The deep integration and real-ti...With the development of information and communication technology and the advent of the Internet of Things(IoT)era,cyber-physical system(CPS)is becoming the trend of products or systems.The deep integration and real-time interaction between the physical world and the virtual world expand system functions.Although there are some CPS implementation guidelines,the virtual world is still relatively abstract compared to the concrete physical world that can be touched through the IoT.Besides that,human is a non-negligible CPS endogenous interactive intelligent component.In this paper,we propose a triple human-digital twin architecture,where the physical objects and the digital twins that are the projections of the physical entities establish the cornerstone of human functioning together.And the hierarchically distributed digital twins grow dynamically with the physical entities along the lifecycle.Furthermore,the interaction and collaboration among the physical objects,the digital twins,and the humans in their respective worlds(the expected world,the interpreted world,and the physical world)integrate the full value chain of the products in anticipation of seamless synergy.Finally,we present a power management digital companion platform for the lunar probe to demonstrate the efficacy of the architecture.展开更多
The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to de...The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.展开更多
Nowadays,more automated or robotic twin-crane systems(RTCSs)are employed in ports and factories to improve material handling efficiency.In a twin-crane system,cranes must travel with a minimum safety distance between ...Nowadays,more automated or robotic twin-crane systems(RTCSs)are employed in ports and factories to improve material handling efficiency.In a twin-crane system,cranes must travel with a minimum safety distance between them to prevent interference.The crane trajectory prediction is critical to interference handling and crane scheduling.Current trajectory predictions lack accuracy because many details are simplified.To enhance accuracy and lessen the trajectory prediction time,a trajectory prediction approach with details(crane acceleration/deceleration,different crane velocities when loading/unloading,and trolley movement)is proposed in this paper.Simulations on different details and their combinations are conducted on a container terminal case study.According to the simulation results,the accuracy of the trajectory prediction can be improved by 20%.The proposed trajectory prediction approach is helpful for building a digital twin of RTCSs and enhancing crane scheduling.展开更多
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 ...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.展开更多
基金supported in part by the National Key Research and Development Program of China(2018AAA0101502,2018YFB1702300)the National Natural Science Foundation of China(61722312,61533019,U1811463,61533017)。
文摘In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.
基金Supported by National Natural Science Foundation of China(Grant Nos.51922041,51835003).
文摘Traditional design,manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost inefective manner.A unifed platform for efcient and intelligent designmanufacturing-maintenance of mechanical equipment and systems is highly needed in this rapidly digitized world.In this work,the defnition of digital twin and its research progress and associated challenges in the design,manufacturing and maintenance of engineering components and equipment were thoroughly reviewed.It is indicated that digital twin concept and associated technology provide a feasible solution for the integration of design-manufacturingmaintenance as it has behaved in the entire lifecycle of products.For this aim,a framework for information-physical combination,in which a more accurate design,a defect-free manufacturing,a more intelligent maintenance,and a more advanced sensing technology,is prospected.
基金supported in part by Shenzhen Key Laboratory of Control Theory and Intelligent Systems (ZDSYS20220330161800001)the National Natural Science Foundation of China (62173255, 62188101)。
文摘With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.
基金supported by the Natural Science Foundation of Jiangsu Province of China under grant no.BK20211284the Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps under grant no.2020DB005.
文摘As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.
基金supported by the Tunisian Ministry of Higher Education and Scientific Research under Grant LSE-ENIT-LR 11ES15funded in part by the PAQ-Collabora(PAR&I-Tk)program。
文摘This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.
基金support received from US Department of Transportation Tier 1 University Transportation Center CREATE Award No.69A3552348330.
文摘With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution systems.Supporting these applications,an important family of methods are based on graphs.For DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of systems.To this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex Systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex systems.The established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision supports.Besides,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the KG.With the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple systems.The bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.
文摘Systems engineering practices are evolving to address fast-changing needs in fielding complex systems.These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by humans’natural capabilities.We propose that systems engineering must aid systems engineering managers by providing architectural alternatives and design options.Further,as systems become more complex and dynamic,there is an increased need to identify hidden risks,model emergent behav-ior,and expose hidden patterns in the behavior of stakeholders.Systems engineering needs to evolve to build fast-fielded,resilient,and adaptive systems that leverage posi-tive reinforcement feedback loops with multiple experimental and real-world information sources.The very basis of systems engineering must evolve from today’s development paradigms to a future that leverages modeling,simulation,and artificial intelligence to drastically improve the capability and agility for developing new systems.This paper proposes a common way forward to enable this new form of complex adaptive systems engineering.
基金funded by National Key R&D Program of China[Grant No.2018YFB1700905]National Defense Basic Scientific Research Program of China[Grant No.JCKY2018203A001].
文摘With the development of information and communication technology and the advent of the Internet of Things(IoT)era,cyber-physical system(CPS)is becoming the trend of products or systems.The deep integration and real-time interaction between the physical world and the virtual world expand system functions.Although there are some CPS implementation guidelines,the virtual world is still relatively abstract compared to the concrete physical world that can be touched through the IoT.Besides that,human is a non-negligible CPS endogenous interactive intelligent component.In this paper,we propose a triple human-digital twin architecture,where the physical objects and the digital twins that are the projections of the physical entities establish the cornerstone of human functioning together.And the hierarchically distributed digital twins grow dynamically with the physical entities along the lifecycle.Furthermore,the interaction and collaboration among the physical objects,the digital twins,and the humans in their respective worlds(the expected world,the interpreted world,and the physical world)integrate the full value chain of the products in anticipation of seamless synergy.Finally,we present a power management digital companion platform for the lunar probe to demonstrate the efficacy of the architecture.
基金This work was funded by the EPSRC Grant"Improving the product development process through integrated revision control and twinning of digital-physical models during prototyping",reference:EP/R032696/1.
文摘The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.
基金This work was supported by the National Natural Science Foundation of China(No.52075036).
文摘Nowadays,more automated or robotic twin-crane systems(RTCSs)are employed in ports and factories to improve material handling efficiency.In a twin-crane system,cranes must travel with a minimum safety distance between them to prevent interference.The crane trajectory prediction is critical to interference handling and crane scheduling.Current trajectory predictions lack accuracy because many details are simplified.To enhance accuracy and lessen the trajectory prediction time,a trajectory prediction approach with details(crane acceleration/deceleration,different crane velocities when loading/unloading,and trolley movement)is proposed in this paper.Simulations on different details and their combinations are conducted on a container terminal case study.According to the simulation results,the accuracy of the trajectory prediction can be improved by 20%.The proposed trajectory prediction approach is helpful for building a digital twin of RTCSs and enhancing crane scheduling.
基金This work is financially supported by the National Key Research and Development Program of China(2016YFB1101700)the National Natural Science Foundation of China(51875030)the Academic Excellence Foundation of BUAA for PhD Students.
文摘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.
