A Model-Based Toolchain to Verify Spatial Behavior of Cyber-Physical Systems

2016 ◽  
Vol 13 (1) ◽  
pp. 40-52 ◽  
Author(s):  
Peter Herrmann ◽  
Jan Olaf Blech ◽  
Fenglin Han ◽  
Heinz Schmidt
Keyword(s):  
Real Time ◽  
Physical Environment ◽  
Spatial Model ◽  
Physical Space ◽  
Cyber Physical Systems ◽  
Spatial Behavior ◽  
Model Checker ◽  
Control Software ◽  
Physical Systems ◽  
Model Based

A method preserving cyber-physical systems to operate safely in a joint physical space is presented. It comprises the model-based development of the control software and simulators for the continuous physical environment as well as proving the models for spatial and real-time properties. The corresponding toolchain is based on the model-based engineering tool Reactive Blocks and the spatial model checker BeSpaceD. The real-time constraints to be kept by the controller are proven using the model checker UPPAAL.

A Model-Based Toolchain to Verify Spatial Behavior of Cyber-Physical Systems

2020 ◽  
pp. 623-637
Author(s):  
Peter Herrmann ◽  
Jan Olaf Blech ◽  
Fenglin Han ◽  
Heinz Schmidt
Keyword(s):  
Real Time ◽  
Spatial Model ◽  
Physical Space ◽  
Cyber Physical Systems ◽  
Spatial Behavior ◽  
Time Constraints ◽  
Model Checker ◽  
Control Software ◽  
Physical Systems ◽  
Model Based

A method preserving cyber-physical systems to operate safely in a joint physical space is presented. It comprises the model-based development of the control software and simulators for the continuous physical environment as well as proving the models for spatial and real-time properties. The corresponding toolchain is based on the model-based engineering tool Reactive Blocks and the spatial model checker BeSpaceD. The real-time constraints to be kept by the controller are proven using the model checker UPPAAL.

Model-Based Development and Spatiotemporal Behavior of Cyber-Physical Systems

2019 ◽  
pp. 69-93
Author(s):  
Peter Herrmann ◽  
Jan Olaf Blech ◽  
Fenglin Han ◽  
Heinz Schmidt
Keyword(s):  
Real Time ◽  
Physical Space ◽  
Cyber Physical Systems ◽  
Control Software ◽  
Actual System ◽  
Time Model ◽  
Physical Systems ◽  
Safety Standards ◽  
Model Based ◽  
Spatiotemporal Behavior

Many cyber-physical systems operate together with others and with humans in a joint physical space. Because of their operation in proximity to humans, they have to operate according to very high safety standards. This chapter presents a method for developing the control software of cyber-physical systems. The method is model-based and assists engineers with spatial and real-time property verification. In particular, the authors describe a toolchain consisting of the model-based development toolset Reactive Blocks, the spatial analyzer BeSpaceD in conjunction with the real-time model checkers UPPAAL and PRISM. The combination of these tools makes it possible to create models of the control software and, if necessary, simulators for the actual system behavior with Reactive Blocks. These models can then be checked for various correctness properties using the analysis tools. If all properties are fulfilled, Reactive Blocks transforms the models automatically into executable code.

scholarly journals A model-based software development method for automotive cyber-physical systems

2011 ◽  
Vol 8 (4) ◽  
pp. 1277-1301 ◽  
Author(s):  
Zhigang Gao ◽  
Haixia Xia ◽  
Guojun Dai
Keyword(s):  
Software Development ◽  
Code Generation ◽  
Physical Environment ◽  
Source Code ◽  
Cyber Physical Systems ◽  
Functional Requirements ◽  
Development Method ◽  
Physical Systems ◽  
Implementation Model ◽  
Model Based

The development of automotive cyber-physical systems (CPS) software needs to consider not only functional requirements, but also non-functional requirements and the interaction with physical environment. In this paper, a model-based software development method for automotive CPS (MoBDAC) is presented. The main contributions of this paper are threefold. First, MoBDAC covers the whole development workflow of automotive CPS software from modeling and simulation to code generation. Automatic tools are used to improve the development efficiency. Second, MoBDAC extracts nonfunctional requirements and deals with them in the implementation model level and source code level, which helps to correctly manage and meet non-functional requirements. Third, MoBDAC defines three kinds of relations between uncertain physical environment events and software internal actions in automotive CPS, and uses Model Modifier to integrate the interaction with physical environment. Moreover, we illustrate the development workflow of MoBDAC by an example of a power window development.

scholarly journals Assurance monitoring of learning-enabled cyber-physical systems using inductive conformal prediction based on distance learning

2021 ◽  
Vol 35 (2) ◽  
pp. 251-264
Author(s):  
Dimitrios Boursinos ◽  
Xenofon Koutsoukos
Keyword(s):  
Neural Networks ◽  
Distance Learning ◽  
Real Time ◽  
Speaker Recognition ◽  
Deep Neural Networks ◽  
Cyber Physical Systems ◽  
Error Rates ◽  
Traffic Sign ◽  
Conformal Prediction ◽  
Physical Systems

AbstractMachine learning components such as deep neural networks are used extensively in cyber-physical systems (CPS). However, such components may introduce new types of hazards that can have disastrous consequences and need to be addressed for engineering trustworthy systems. Although deep neural networks offer advanced capabilities, they must be complemented by engineering methods and practices that allow effective integration in CPS. In this paper, we proposed an approach for assurance monitoring of learning-enabled CPS based on the conformal prediction framework. In order to allow real-time assurance monitoring, the approach employs distance learning to transform high-dimensional inputs into lower size embedding representations. By leveraging conformal prediction, the approach provides well-calibrated confidence and ensures a bounded small error rate while limiting the number of inputs for which an accurate prediction cannot be made. We demonstrate the approach using three datasets of mobile robot following a wall, speaker recognition, and traffic sign recognition. The experimental results demonstrate that the error rates are well-calibrated while the number of alarms is very small. Furthermore, the method is computationally efficient and allows real-time assurance monitoring of CPS.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

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