17 results about "Cyber-physical system" patented technology

The invention discloses an Internet of Vehicles computing unloading method and system based on information age and privacy protection, and the method comprises the steps: building an optimization problem with information age and energy consumption as targets through building a vehicle task model and an energy consumption time delay model, and introducing a geographical undistinguishable constraint to protect location privacy, and the real position of the vehicle is disturbed by using a planar Laplace mechanism. And modeling calculation unloading as a Markov decision process, and selecting an unloading strategy by an intelligent agent based on the disturbed position information, environment state and task characteristics. And solving by adopting a GRPO reinforcement learning algorithm, updating the strategy network based on advantage estimation and KL divergence constraint, and obtaining an optimal unloading decision. According to the method, collaborative optimization of privacy security, information freshness and energy efficiency in the Internet of Vehicles is realized through information age modeling, geographical indistinguishability location disturbance and GRPO reinforcement learning.

Computer-implemented methods and systems for training an adversarial neural network to simulate a stealthy blind false data injection attack on a cyber physical system are provided. Supervised learning is used to generate an initial attack vector, by an adversarial attack generation model, based on inferred grid topology and historical measurements. A final attack vector is generated, by an adversarial verification model, based on a filtered subset of the initial attack vector utilizing a substitute bad data detection threshold, wherein the final attack vector enables creation of a counter measure.

The present invention relates to a method for error detection and handling in a DevOps-pipeline for a cyber physical system and related system. The method comprising the steps of: writing and committing code destined to be used for monitoring and / or controlling operations of components of the CPS; compiling the code and packaging it into deployable units; deploying the code per deployable unit into one or more component of the CPS; connecting one or more domain-specific language, DSL, elements to respective one or more CPS components; gathering data from the respective one or more CPS components by the one or more DSL elements; processing by the one or more DSL elements the data gathered in a format of the respective one or more CPS component; comparing by the one or more DSL element the processed data to a predefined failure condition to detect a failure.

The application relates to a power grid cyber physical system protection method. The method comprises the following steps: determining an attack scene based on the structure of a power grid cyber physical system (CPPS) interaction model, wherein different attack scenes correspond to different attack targets and defense targets; obtaining a CPPS vulnerability evaluation framework based on the defense target of the attack target in different attack scenes; obtaining a CPPS active load loss model based on Newton-Raphson power flow calculation equations and preset power constraint conditions; obtaining the defense resources allocated to the attack target based on the CPPS vulnerability evaluation framework and the CPPS active load loss model; establishing a CPPS attack and defense game model and designing an attack and defense game scene based on the structure of the CPPS interaction model and the defense resources allocated to the attack target; and obtaining a CPPS protection scheme based on game theory. The method can consider the structure of the power grid cyber physical system interaction model and give an optimal defense resource allocation strategy.

The present invention relates to a video monitoring method in an area where a plurality of CCTV cameras is installed, such as an urban area. As a digital twin Cyber Physical System (CPS) is constructed, and a control server connected to a camera and a computer connected to the control server are configured, and a model object generated from a CPS model and video information transmitted from the camera are collected in the control server and transmitted to the computer, users may confirm a digital twin-based model object together with actually captured video information. Through the present invention, it is possible to immediately and clearly confirm surrounding spaces, as well as the location of a camera transmitting specific video information in video monitoring of a wide area such as urban areas, and efficiency and accuracy of viewing the video information of a plurality of cameras can be dramatically improved.

The application relates to the technical field of smart power grids, and is a multi-dimensional dynamic elasticity identification method and system for a key coupling node of a power distribution information physical system. The system comprises a key node screening unit, a unified CPDS model is constructed, and a candidate key node set is preliminarily screened based on structural controllability and structural observability; a fuzzy scene generation unit is used to construct a dynamic fuzzy disaster scene set by using a Markov chain Monte Carlo method, and a set containing a large number of dynamic fuzzy disaster scenes is generated; an elasticity function construction unit; a node calculation output unit; the application proposes a new CPDS key coupling node accurate identification method which is fused with structural controllability, structural observability, dynamic fuzzy disaster scenes, reverse reinforcement learning and Shapley value comprehensive calculation, so that the accuracy, fairness and adaptability of system elasticity analysis and decision-making are improved, and the fast response and recovery capability of the power grid to disasters or attack disturbances is improved.

Systems and methods are provided for incident analysis in Cyber-Physical Systems (CPS) using a Temporal Graph-based Incident Analysis System (TGIAS) and / or Transition Based Categorical Anomaly Detection (TCAD). Dynamically gathered multimodal data from a distributed network of sensors across the CPS are preprocessed to identify abnormal sensor readings indicative of potential incidents, and a multi-layered incident timeline graph, representing abnormal sensor readings, relationships to specific CPS components, and temporal sequencing of events is constructed. Severity scores are calculated, and severity rankings are assigned to identified anomalies based on a composite index including impact on CPS operation, comparison with historical incident data, and predictive risk assessments. Probable root causes of incidents and pathways for anomaly propagation through the CPS are identified using causal interference and the incident timeline graph to detect underlying vulnerabilities and predict future system weaknesses. Recommended actions are generated and executed for incident resolution and system optimization.

The invention provides a meta-model-based Casseblog physical system logic architecture generation method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, the method comprises the following steps: obtaining a user demand of a Casseblog physical system, and decomposing the user demand into a plurality of core sub-demands; according to the plurality of core sub-requirements, determining the system capability of the Casseblog physical system; based on the system capability, carrying out operation scene analysis through a basic function meta-model of the Caibo physical system, and determining system activities of the Caibo physical system; instantiating the system activity based on the basic function meta-model of the cyber physical system to generate a system function instantiation model; the system function instantiation model is analyzed and clustered, and the logic architecture of the Cassebo physical system is generated. Through the method provided by the invention, the logic architecture conforming to the system capability is automatically generated, the derivation efficiency is improved, and the risk of inter-domain interaction logic missing is avoided.

Systems and methods are provided for incident analysis in Cyber-Physical Systems (CPS) using a Temporal Graph-based Incident Analysis System (TGIAS) and / or Transition Based Categorical Anomaly Detection (TCAD). Dynamically gathered multimodal data from a distributed network of sensors across the CPS are preprocessed to identify abnormal sensor readings indicative of potential incidents, and a multi-layered incident timeline graph, representing abnormal sensor readings, relationships to specific CPS components, and temporal sequencing of events is constructed. Severity scores are calculated, and severity rankings are assigned to identified anomalies based on a composite index including impact on CPS operation, comparison with historical incident data, and predictive risk assessments. Probable root causes of incidents and pathways for anomaly propagation through the CPS are identified using causal interference and the incident timeline graph to detect underlying vulnerabilities and predict future system weaknesses. Recommended actions are generated and executed for incident resolution and system optimization.

The application discloses an architecture design method and device of an intelligent automobile cyber-physical system and related equipment. It relates to the technical field of vehicles and road traffic. The method comprises the following steps: obtaining the architecture design requirements of the intelligent automobile cyber-physical system; in response to the architecture design requirements, constructing the view architecture of each perspective according to the metamodel of each view in the preset system architecture framework under multiple perspectives, and obtaining the initial architecture model of the intelligent automobile cyber-physical system; and simulating and optimizing the initial architecture model to obtain the target architecture model of the intelligent automobile cyber-physical system. According to the embodiment of the application, the design path and output standard are specified by a unified architecture framework, the design language and understanding, design boundary and analysis granularity of multiple participants are unified, and the design consensus of multiple stakeholders is reached.

The application discloses an active distribution network cyber physical system (ADNCPS) operation situation prediction method and system against network attacks, constructs an ADNCPS situation prediction index system, sets alarm threshold values for various indexes in the index system, stores real-time acquired ADNCPS operation data into a historical data storage module, completes the screening and calculation of initial ADNCPS operation data by using the constructed ADNCPS situation prediction index system, compares the calculation results with the alarm threshold values of various prediction indexes, stores the index data exceeding the alarm threshold values according to time sequences, completes the prediction of various indexes by using a model parallel situation prediction model based on CNN-LSTM, and finally completes the operation situation prediction of the ADNCPS by using a fuzzy analytic hierarchy process method. The application improves the prediction accuracy and provides protection for the safe and stable operation of the ADNCPS.

A motion and process cooperative control industrial information physical system adopts a multi-layer life body type system architecture and modeling and is composed of five layers, namely a man-machine interaction layer, a global intelligent optimization layer, a dynamic reconstruction layer, a hybrid control layer and a physical layer from top to bottom; each layer has a specific function, and the three middle layers (a global intelligent optimization layer, a dynamic reconstruction layer and a hybrid control layer) and all layers under the three layers form a global intelligent optimization ring, a dynamic reconstruction ring and a hybrid control ring, so that multi-layer feedback and optimization are realized; deep coupling of motion control and process control is realized through a dynamic reconstruction ring and a hybrid control ring, and real-time interaction of mechanical motion (such as a multi-axis unit) and process parameters (temperature / pressure and the like) is supported; in combination with discrete Petri net modeling and continuous dynamic equation modeling, adaptive conversion of a system state is realized through discrete-to-continuous mapping and continuous-to-discrete triggering.

The invention relates to the technical field of power distribution network safety, and discloses a disaster resisting method and device based on a power distribution information physical system, and a storage medium, and the method comprises the steps: obtaining a composite fault scene set of power failure of a communication base station caused by the interruption of a power distribution line, and taking the minimum sum of the loss loads of all nodes as an optimization target when the composite fault degree is maximum; constructing an optimization objective function; constructing a reinforced resource quantity constraint, an active power balance constraint including a communication base station shutdown constraint, and a remote control enabling constraint; forming a target disaster defense strategy model with reactive power balance constraint, branch voltage drop constraint, line bearing capacity constraint, line on-off power flow constraint, fault logic constraint, voltage amplitude constraint, load reduction constraint and reconstruction constraint of the distribution line; and solving to obtain an optimal disaster resisting scheme, and reinforcing the target distribution line.

A vehicle-network interaction electric power cyber physical system risk assessment method, through the detection of vehicle-network interaction electric power cyber physical system false data injection attack, and based on the attack benefit, a risk assessment of vehicle-network interaction electric power cyber physical system subjected to false data injection attack is designed, which can estimate the current system state, and is beneficial to the next time state prediction of system regulation and control, and promotes vehicle-network interaction electric power system management.

This invention discloses an operation and scheduling method and system for distribution network cyber-physical systems, relating to the field of distribution network operation control and scheduling technology. It acquires physical operation status information of the distribution network and operation status information of the information system. Based on the radial topology of the distribution network, a linearized DistFlow model is used to describe branch power balance and node voltage constraints. Combined with the operation status information of the information system, control executability constraints are constructed to form a dynamic state evolution model. With the objective of minimizing the sum of operational economy, operational deviation, and information-constrained risk penalties, a scheduling optimization model is constructed and solved to obtain candidate scheduling control vectors. These candidate scheduling control vectors are processed through gating correction and amplitude contraction mechanisms to obtain the final scheduling control vector. Dynamic correction and rolling updates are performed based on real-time state feedback. This invention significantly improves the scheduling reliability and economy of distribution systems in high-penetration renewable energy scenarios through strong cyber-physical coupling modeling and rolling optimization mechanisms.

Complexities arising from interaction between multiple inter-connected components in an autonomous cyber physical system can potentially result in differences in intended and observed operations of a CPS. To perform fault analysis of a CPS it is imperative to explain this discrepancy in terms of the components of CPS control code. A system estimates a “mined” hybrid system representation of a CPS based on observed input / output traces and extracts a state machine representation of the CPS control code. The system compares the “mined” hybrid system representation with the extracted state machine representation simplification of the CPS code to identify discrepancies between expected and observed operation of the CPS. The system explains discrepancies in terms of call conditions as binary or unary operations on input and output variables and status of function call arguments.