Simulation Of Cyber-physical Systems Research Articles

Review on the key technologies of power grid cyber‐physical systems simulation

AbstractA Cyber‐Physical System (CPS) is a spatiotemporal multi‐dimensional and heterogeneous hybrid autonomous system composed of deep integration of information resources and physical systems. With the development of digitisation and digitalisation, a large number of data acquisition equipment, computing equipment, and electrical equipment are interconnected between the power grid and the information communication network. The power grid has thus been restructured as a mature and highly complex CPS. In order to promote the development of power grid CPS technologies and provide a reference for relevant researchers in the field, the origin and concept of CPS and features in power grid CPS are introduced firstly. Then the key technologies of power grid CPS simulation are discussed and further analysed from three perspectives, including modelling theory, simulation methods, and system‐level simulation. On this basis, the application of CPS simulation technology in future power grids has been prospected.

가상 센서 기반 재공 위치 추정 방법 연구

This paper presents the estimation methodology of position of WIP(Work-In-Process). Since the monitoring digital twin synchronizes with a real manufacturing system, it is essential for the CPS (Cyber-Physical System) simulation or on-line simulation. A CPS simulator needs to start a simulation execution for any given time ‘t’, which requires the exact ‘snap-shot’ of the real manufacturing system at time ‘t’. The snapshot is the total state of the manufacturing system including all states of manufacturing facilities as well as all position of WIPs. This paper proposes the estimation methodology of position of WIPs which can provide the snapshot of a manufacturing system, and the proposed methodology is based on the concept of virtual sensors. If all WIPs in the system have virtual sensors attached, the movement of the WIP is defined according to other virtual sensor data and the mechanism of the facility. To verify the performance of these estimation methods, positions are compared for the same WIP in simulation and monitoring.

Robust Simulation of Cyber-Physical Systems for Environmental Monitoring on Construction Sites

Environmental monitoring is a crucial part of environmental management on construction sites. With the increasing integration of environmental-monitoring systems and cyber-physical systems (CPS), the environmental-monitoring cyber-physical system (E-CPS) has been developed, but it still suffers from uncertainty problems and a lack of robustness. In this study, ontology is utilized to establish an E-CPS model that can realize the integration and interaction of physical space, cyberspace, and social space, and the E-CPS model contains perception, transportation, fusion, and decision-making layers. Three uncertainty scenarios are then identified in four layers of the E-CPS to address the current E-CPS shortcomings. The proposed E-CPS model is applied in a construction project, and simulation experiments are then conducted on construction sites. The results show that the abnormal-data-recognition algorithm based on spatiotemporal correlation, whose detection rate is stable around 96%, improves the system’s anti-interference ability against anomalous data entering the perception layer and the transportation layer. This algorithm ensures the accuracy of environmental monitoring for early warning. The sensory data-fusion results based on the belief function method vary from 52.16 to 52.50, with a decrease rate reduced to 0.65%. Finally, the decision-fusion algorithm based on the improved Dempster–Shafer (D-S) evidence theory achieves robust performance. This study could enhance the robustness of the E-CPS in uncertainty conditions and aid the project managers to make decisions and take targeted measures according to the environmental monitoring results and experts’ decisions.

Proving Simulink Block Diagrams Correct via Refinement

Simulink is a well-known block diagram-based tool for modular design and multidomain simulation of Cyber-Physical Systems (CPS). However, the simulation by Simulink cannot completely cover the state space or behavior of a target system, which would not ensure the correctness of the developed block diagrams in Simulink. In this work, we present a contract-based method, which supports compositional reasoning and refinement, for proving the correctness of Simulink block diagrams with discrete-time and continuous-time dynamic behavior. We use the assume-guarantee contract as a specification language. The Simulink block diagrams are correct in the sense that if the block diagrams satisfy the formal specifications of the system being modeled. To prove the correctness of a block diagram, we first define semantics for Simulink block diagrams. We study three composition operators, i.e., serial, parallel, and algebraic loop-free feedback with multistep delays. We present a satisfaction relation between the block diagram and contract and present a refinement relation between the contracts. We prove that if the Simulink block diagram satisfies the composition contract and the composition contract refines the system specifications, the block diagram is correct relative to the system specifications. Furthermore, we demonstrate the effectiveness of our method via a real-world case study originating from the control system of a reservoir. Our method can also provide an idea to verify whether the designed CPS is planted with a logic bomb by attackers.

Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Cyber-physical systems (CPSs) integrate heterogeneous systems and process sensor data using digital services. As the complexity of CPS increases, it becomes more challenging to efficiently formalize the integrated multidomain views with flexible automated verification across the entire lifecycle. This article illustrates a model-based systems engineering tool-chain to support CPS development with an emphasis on automated parameter value selection for co-simulation. First, a domain-specific modeling approach is introduced to support the formalizations of CPS artifacts, development processes, and simulation configurations. The domain-specific models are used as the basis to generate a Web-based process management system for automated parameter value selections, which coordinates Open Services for Lifecycle Collaboration services of development information and technical resources (models, data, and tools) in order to support automated co-simulation. The services are deployed by a service orchestrator based on a decision-making algorithm for parameter value selection. Finally, developers make use of the WPMS to implement simulations and to select system parameter values for co-simulation automatically. The approach is illustrated by a case study on auto-braking system development and we evaluate the efficiency of this tool-chain by both qualitative and quantitative methods. The results show that parameter values are selected more efficiently and effectively when implementing co-simulations using our tool-chain.

Simulation-oriented model reuse in cyber-physical systems: A method based on constrained directed graph

Modeling and Simulation of Cyber-Physical Systems (MSCPS) is demanding in terms of immediate response to dynamic and complex changes of CPS. Simulation-oriented model reuse can be used to build a whole CPS model by reusing developed models in a new simulation application, which avoid repeated modeling and thus reduce the redevelopment of submodels. Model composition, one of the important methods, enables model reuse by selecting and adopting diversified integration solutions of simulation components to meet the requirements of simulation application systems. In this paper, a real-time model integration approach for global CPS modeling is proposed, which reuses developed submodels by compositing submodel nodes. Specifically, a constrained directed graph of submodels for the whole system which can meet the simulation requirements is constructed by reverse matching. Submodel properties, including co-simulation distance between submodel nodes, reuse benefit and simulation performance of model nodes, are quantified. Based on the properties, the model-integrated solution for the whole CPS simulation is retrieved throughout the model constrained digraph by the Genetic Algorithm (GA). In the experiment, the proposed method is applied to a typical model integrated computing scenario containing multiple model-integration solutions, among which the Pareto optimal solutions are retrieved. Results show that the effectiveness of the model integration method proposed in this paper is verified.

Industrial Datasets with ICS Testbed and Attack Detection Using Machine Learning Techniques

Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped with real-time attacks using in-house penetration test tool with reconnaissance, interception, and firmware analysis scenarios. The test cases with different real-time hacking scenarios are implemented with the ICS cyber test kit, and its industrial datasets are captured which can be utilized for Deep packet inspection (DPI). The DPI provides more visibility into the contents of OT network traffic based on OT protocols. The Machine learning (ML) techniques are deployed for cyber-attack detection of datasets from the cyber kit. The performance metrics such as accuracy, precision, recall, F1 score are evaluated and cross validated for different ML algorithms for anomaly detection. The decision tree (DT) ML technique is optimized with pruning method which provides an attack detection accuracy of 96.5%. The deep learning (DL) techniques has been used recently for enhanced OT intrusion detection performances.

Parallel simulation of cyber-physical systems

Model-based design (MBD) in systems engineering is a well-accepted technique to abstract, analyze, verify, and validate complex systems. In MBD, we design a mathematical model of the system to virtually execute and test systems via model simulations to understand the system dynamics better. Computing model simulations has their challenges; one is to ensure that the simulation trajectory preserves the model semantics. Besides, computing many simulation trajectories over a long time-horizon must be time efficient for rapid respond to system engineers. In this work, we address these challenges in simulating models of cyber-physical systems (CPS), particularly systems possessing mixed discrete–continuous dynamics. We focus on the subclass of CPS’s hybrid automata models, where Jump predicates are restricted to polygonal constraints and present a numerical simulation engine that can efficiently compute many random simulations in parallel by exploiting the parallel computing capability in modern multicore processors. Our simulation engine implements a lock-free parallel breadth-first-search (BFS)-like algorithm and is implemented in the model-checking tool XSpeed. In addition, an application of our simulation engine in property verification of CPS models has been illustrated on two benchmarks. Some model coverage metrics have been defined that users of the tool can specify to set the desired thoroughness of testing with simulations. We demonstrate the performance gains of our simulation engine over SpaceEx and CORA, the modern model checkers and simulators for affine hybrid systems.

Comprehensive fault simulation method in active distribution network with the consideration of cyber security

With the many characteristics of cyber–physical systems (CPS), including the complex evolution of various dynamic processes in distribution networks (DNs), communication modes and serious network security events have become important issues. From the perspective of DN analysis, traditional electrical digital simulations cannot access current models of communication systems and cyber network security events. The interactions between cyber and physical networks cannot be simulated and analysed simultaneously, which is challenging to the development of CPS simulations of DNs. To evaluate the impact of cyber networks on physical networks, a CPS simulation platform that contains physical, communication and control layers is discussed. Three-phase short-circuit fault processing and islanding operation control are simulated by data interactions among three-layer models that are used to analyse the impact of communication data tampering on fault handling processes. The influence of data tampering on fault processing and the influence of false data injection and data interception on islanding operation control processes are analysed. The simulation results show that the network information security has a large impact on fault protection and islanding operation control, which leads to the expansion of the outage scope and the failure of islanding operation frequency adjustment. This article also provides a simulation basis for the analysis of CPS operation characteristics and the identification and prevention of cyber network security events.

Reconciling interoperability with efficient Verification and Validation within open source simulation environments

A Cyber–Physical System (CPS) comprises physical as well as software subsystems. Simulation-based approaches are typically used to support design and Verification and Validation (V&V) of CPSs in several domains such as: aerospace, defence, automotive, smart grid and healthcare.Accordingly, many simulation-based tools are available to support CPS design. This, on one side, enables designers to choose the toolchain that best suits their needs, on the other side poses huge interoperability challenges when one needs to simulate CPSs whose subsystems have been designed and modelled using different toolchains. To overcome such an interoperability problem, in 2010 the Functional Mock-up Interface (FMI) has been proposed as an open standard to support both Model Exchange (ME) and Co-Simulation (CS) of simulation models created with different toolchains. FMI has been adopted by several modelling and simulation environments. Models adhering to such a standard are called Functional Mock-up Units (FMUs). Indeed FMUs play an essential role in defining complex CPSs through, e.g., the System Structure and Parametrisation (SSP) standard.Simulation-based V&V of CPSs typically requires exploring different simulation scenarios (i.e., exogenous input sequences to the CPS under design). Many such scenarios have a shared prefix. Accordingly, to avoid simulating many times such shared prefixes, the simulator state at the end of a shared prefix is saved and then restored and used as a start state for the simulation of the next scenario. In this context, an important FMI feature is the capability to save and restore the internal FMU state on demand. This is crucial to increase efficiency of simulation-based V&V. Unfortunately, the implementation of this feature is not mandatory and it is available only within some commercial software. As a result, the interoperability enabled by the FMI standard cannot be fully exploited for V&V when using open-source simulation environments. This motivates developing such a feature for open-source CPS simulation environments.Accordingly, in this paper, we focus on JModelica, an open-source modelling and simulation environment for CPSs based on an open standard modelling language, namely Modelica. We describe how we have endowed JModelica with our open-source implementation of the FMI 2.0 functions needed to save and restore internal states of FMUs for ME. Furthermore, we present experimental results evaluating, through 934 benchmark models, correctness and efficiency of our extended JModelica. Our experimental results show that simulation-based V&V is, on average, 22 times faster with our get/set functionality than without it.

Guaranteed master for interval-based cosimulation

In this paper, we tackle the problem of guaranteed simulation of cyber-physical systems, an important model for current engineering systems. Their is always increasing complexity which leads to models of higher and higher dimensions, yet typically involving multiple subsystems or even multiple physics. Given this modularity, we more precisely explore cosimulation of such dynamical systems, with the aim of reaching higher dimensions of the simulated systems. In this paper, we present a guaranteed interval-based approach for cosimulation of continuous time systems. We propose an algorithm which first proves the existence and returns an enclosure of global solutions, using only local computations. This mitigates the curse of dimensionality faced by global (guaranteed) integration methods. Local computations are then realized with a safe estimate of the other sub-systems until the next macro-step. We increase the accuracy of the approach by using an interval extrapolation of the state of the other sub-systems. We finally propose some possible further improvements including adaptive macro-step size. Our method is fully guaranteed, taking into account all possible sources of error. It is implemented in a C++ prototype relying on the DynIbex library, and we illustrate our approach on multiple examples of the literature.

A Multi-Layer Architecture for Near Real-Time Collaboration during Distributed Modeling and Simulation of Cyberphysical Systems

Abstract We present a Web-based multi-layer architecture and implementation to enable near real-time collaboration within partially-distributed engineering teams in this paper. Our architecture named Distributed Modeling and Simulation (DisMoSim) enables collaborative 3D modeling and simulation of complex cyberphysical systems (CPS) across different servers, offices, lab spaces, or organizations. More specifically, DisMoSim creates networks of DisMoSim nodes that communicate using Web protocols with little or no perceptible delay. Each node provides different CPS services, e.g., user interface nodes provide collaborative 3D modeling; computational nodes provide simulations of multi-body dynamics or kinematics; storage nodes allow persisting and sharing models and simulation results; hardware-in-the-loop nodes connect physical testing workbenches to provide real-world sensor measurements as simulation input; software-in-the-loop nodes provide control signals to simulate hardware controllers. In the following, we derive a set of design goals and propose our DisMoSim architecture. We illustrate how we used our multi-layer conceptual architecture to implement a variety of CPS services for an example scenario. By this, we demonstrate the practicability and versatility of our approach and conclude by discussing limitations and future work.

Applying ergonomics within the multi-modelling paradigm with an example from multiple UAV control

This article presents a position statement on using ergonomics in conjunction with the multi-modelling paradigm. Multi-modelling is a computational approach to combine models of systems and components for design and simulation of cyber physical systems and systems of systems. Despite potentially significant benefits in terms of more human-centric system modelling, there is limited evidence of the application of ergonomics within multi-modelling. This article presents the case for applying ergonomics within multi-modelling. We open with an introduction to multi-modelling and benefits, applications and gaps for ergonomics in multi-modelling, and of potentially useful models from ergonomics. We then describe a proof-of-concept implementation of ergonomics within a multi-model of UAV control. This demonstrates that as well as user-centred modelling, this approach supports ergonomics in how we can access rich systems models, and the collaborative value of applying ergonomics theory in systems design. Practitioner Summary: Examines multi-modelling, a computational approach for complex modelling, and the contribution of ergonomics. An autonomous UAV test implementation demonstrates the application of ergonomics knowledge for improving design and evaluation processes, and how multi-modelling can give ergonomics access to rich systems models. Abbreviations: ACT-R: adaptive control of thought—rational; API: application programming interface; CFD: computational fluid dynamics; COTS: commerical off the shelf; CPS: cyber-physical system; CT: continuous time; DE: discrete event; DSE: design space exploration; FME: finite element modeling; FMI: functional mock-up interface; FMU: functional mock-up unit; GOMS: goals, operators, methods, selections; HCI: human-computer interaction; IMPRINT: improved performance research integration tool; INTO-CPS: integrated toolchain for cyber-physical system modeling; KLM: keystroke level model; MPC: model-predictive control; SysML: system markup language; SoS: system of system; UAV: unmanned aerial vehicle

A dynamic Quantized State System execution framework for Hybrid Automata

Cyber–physical Systems (CPS) involve a network of discrete controllers that control physical processes, e.g., pacemakers controlling the heart rhythm. The intuitive and formal Hybrid Automata (HA) based modelling approach for CPS is gaining momentum. HA combines the model of the plant along with its discrete controller resulting in a piece-wise continuous system with discontinuities. Accurate detection of these discontinuities, using appropriate level crossing detectors, is a key challenge to simulation of CPS modelled in HA. Existing techniques employ time discrete numerical integration with bracketing for level crossing detection. These techniques involve back-tracking and are highly non-deterministic and hence error prone. As level crossings happen based on the values of continuous variables, Quantized State System (QSS)-integration may be more suitable.We propose a dynamic quanta based execution framework for HA. A CPS modelled as a HA is first translated into the proposed formal intermediate format called the Quantized State Hybrid Automata (QSHA). The QSHA is then executed using a discrete event simulation algorithm based on quantized state semantics. The developed formal model and the associated simulation framework guarantees that: ① all level crossings are accurately detected and ② the time of the level crossing is also accurate within floating point error bounds. Interestingly, benchmark results reveal that the proposed simulation technique takes 720, 2.17, 1.33 and 4.41 times fewer simulation steps compared to QSS-1, QSS-3, Runge–Kutta (RK)-45, and Differential Algebraic System Solver (DASSL) integration based techniques, respectively.

F-DCS: FMI-Based Distributed CPS Simulation Framework with a Redundancy Reduction Algorithm

A cyber physical system (CPS) is a distributed control system in which the cyber part and physical part are tightly interconnected. A representative CPS is an electric vehicle (EV) composed of a complex system and information and communication technology (ICT), preliminary verified through simulations for performance prediction and a quantitative analysis is essential because an EV comprises a complex CPS. This paper proposes an FMI-based distributed CPS simulation framework (F-DCS) adopting a redundancy reduction algorithm (RRA) for the validation of EV simulation. Furthermore, the proposed algorithm was enhanced to ensure an efficient simulation time and accuracy by predicting and reducing repetition patterns involved during the simulation progress through advances in the distributed CPS simulation. The proposed RRA improves the simulation speed and efficiency by avoiding the repeated portions of a given driving cycle while still maintaining accuracy. To evaluate the performance of the proposed F-DCS, an EV model was simulated by adopting the RRA. The results confirm that the F-DCS with RRA efficiently reduced the simulation time (over 30%) while maintaining a conventional accuracy. Furthermore, the proposed F-DCS was applied to the RRA, which provided results reflecting real-time sensor information.

Implementation and Simulation of Cyber Physical System for Robotic Arm Control in Smart Factory

제4차 산업혁명시대의 제조 및 생산 라인 내부의 프로세스는 IoT 및 관련 임베디드 시스템을 통해 공정 내 제품 정보 및 상태를 파악하고, 각 시스템들의 상호연결을 통해 전체 프로세스 주기를 실시간으로 파악할 수 있다. 이러한 시스템 내에서 병목 현상과 문제점을 파악하는 것은 사이버 물리적 시스템 (CPS)의 주된 기능 중의 하나이다. 이 연구에서는 생산현장에서 마이크로 프로세서로 제어되는 로봇 팔의 사이버 물리적 시스템 구현을 통해, 로봇팔이 포함된 전 생산 프로세스를 제어하고 최적화하는데 초점을 둔다. 본 연구에서 구현한 프레임 워크는 다이나믹하게 변화되는 생산환경을 센서를 통하여 CPS로 전송하여, 장착된 시뮬레이션 기능을 통하여 사이클 타임을 추정하고, 이를 목표 사이클 타임과 비교한다. 이때 생기는 차이를 줄이기 위하여, 로봇 파라미터의 조합을 통한 효과적인 솔루션을 도출하고, 이를 로봇 팔의 제어에 적용한다. 제안 된 프레임 워크는 실시간 시뮬레이션 및 제어를 가능하게 하며, 동시에 다양한 시나리오를 테스트할 수 있는 테스트베드로 사용 가능하다.

On model of cyber-physical system with state and measurement attacks on the basis of stochastic difference equations

The article is devoted to questions of simulation of cyber-physical systems taking into account information threats. The principles of organization of structure and reliable functioning of the studied systems are analyzed. The conceptual model of cyber-physical systems taking into account information threats is presented. The constructive algorithm for finding an estimation in a cyberphysical model during attacks on a state and observation on the basis of measuring system indices is proposed in the work. The model is presented as a non-stationary descriptor system, which includes differential equations for node state variables and algebraic equations for measurements. State variables and measurements are considered as random vectors. The information criterion is used to find the optimal estimate of the scalar product that characterizes the state of the system. The algorithm is based on the construction of the task of estimation to the problem of optimal control. The value of the mean square error that does not depend on attacks is obtained. The evaluation was carried out in the form of a scalar product, which includes a measurement vector. An algorithm for constructing an optimal estimation for a scalar product is proposed, which includes the state of the network model during an attack. Mutual information between random vectors was used as a quality criterion for optimization. The evaluation was carried out in the form of a scalar product, which includes a measurement vector. Considering the effects of attacks on this estimate, it should be noted that the build estimate depends on such attacks only through the multiplier. The average square error of such an estimate is independent of the attack. The reason for the absence of impact of the attack on the mean square error is the quadratic form of the sets that are selected for state attacks. This assumption makes it possible to apply a linear-quadratic optimization device, which reduces the problem of evaluation to the problem of optimal control. Received results illustrated in the numerical example for the stage of system without noise and with attacks and for the stage of system with noise and attacks. In this case , a three-node cyberphysical system was used which could be used for planning technical service and optimized management for achievement more high totalperformance and safety of the studied systems .

On the Approaches to Cyber-physical Systems Simulation

On the Approaches to Cyber-physical Systems Simulation

A Novel Error Correction Mechanism for Energy-Efficient Cyber-Physical Systems in Smart Building

Smart building is an effective solution to address the issue of energy consumption in today’s cyber-physical systems (CPSs) connected world. As an important tool to collect information from a fleet of electric appliance that installed in the building scope, a wireless sensor network is widely employed for this purpose. In this paper, we propose to incorporate forward error correction into the media access control layer of IEEE 802.15.4 standard for packets transmission, as the originally used automatic repeat request mechanism is a timing and energy consumed process that should be avoided in a noisy wireless channel of a smart building environment. Based on the developed CPS simulation platform, the bits error rate and packets error rate of convolutional codes (CCs), Reed-Solomon (RS) codes, and their concatenated codes are intensively investigated, on condition of been applied to different packet length and code rates. We show that the CCs are superior to other codes in most cases. However, the RS and CCs concatenated codes are good candidates, and the RS codes with larger symbol length are preferred for a longer packet. In this regard, future research will concentrated on non-line-of-sight wireless channel, and take the pulse interference from other devices into account.

A model-based design approach for simulation and virtual prototyping of automotive control systems using port-Hamiltonian systems

Cyber–physical systems (CPS) such as automotive control systems consist of various interacting cyber and physical components. Heterogeneous domains, composition of multiple components, complex dynamics, and nonlinearities result in significant challenges for design, modeling, and simulation of CPS. Model-based design can be used to address such challenges, but it is very important to use physically accurate heterogeneous models that can be composed to represent the overall system behavior. Further, it is important to preserve the properties derived from analyses based on the mathematical models in the control system implementation in order to reduce costly testing and design changes late in the development cycle. This paper proposes a model-based design methodology for automotive control software using port-Hamiltonian systems (PHS). PHS are used to model the vehicle dynamics, speed and steering control systems, and the interactions between physical and cyber components. Passivity analysis is used to design the controllers and ensure system stability. More importantly, the proposed approach guarantees that passivity is preserved after time-discretization and quantization of the controllers. The models are then used for code generation and compilation, scheduling, and software deployment, ensuring that passivity is preserved by the control system implementation. We evaluate the methodology using an automotive control design case study implemented on a hardware-in-the-loop simulation platform and present simulation results to demonstrate its effectiveness.