High Level Design of a Home Autonomous System Based on Cyber Physical System Modeling

2017 ◽  
Author(s):  
Basman M. Hasan Alhafidh ◽  
William H. Allen
Keyword(s):  
Physical System ◽  
Autonomous System ◽  
System Modeling ◽  
Cyber Physical System ◽  
Level Design ◽  
High Level

Control-theoretic cyber-physical system modeling and synthesis

2012 ◽  
Vol 11 (4) ◽  
pp. 1-24 ◽  
Author(s):  
Donghwa Shin ◽  
Jaehyun Park ◽  
Younghyun Kim ◽  
Jaeam Seo ◽  
Naehyuck Chang
Keyword(s):  
Physical System ◽  
System Modeling ◽  
Cyber Physical System

Cyber-Physical System Modeling for Assessment and Enhancement of Power Grid Cyber Security, Resilience, and Reliability

2020 ◽  
pp. 237-270
Author(s):  
Bart W. Tuinema ◽  
José L. Rueda Torres ◽  
Alexandru I. Stefanov ◽  
Francisco M. Gonzalez-Longatt ◽  
Mart A. M. M. van der Meijden
Keyword(s):  
Cyber Security ◽  
Physical System ◽  
System Modeling ◽  
Power Grid ◽  
Cyber Physical System

High-Level Design and Implementation of a Home Autonomous System Based on CPS Modeling

2018 ◽  
pp. 121-142
Author(s):  
Basman M. Alhafidh ◽  
William H. Allen
Keyword(s):  
Smart Home ◽  
Autonomous System ◽  
Machine Learning Algorithms ◽  
Design And Implementation ◽  
Use Of Resources ◽  
User Data ◽  
Level Design ◽  
High Level ◽  
Accuracy Of Prediction ◽  
User Actions

The process used to build an autonomous smart home system based on cyber-physical systems (CPS) principles has recently received increased attention from researchers and developers. However, there are many challenges to be resolved before designing and implementing such a system. In this chapter, the authors present a high-level design approach that simulates a smart home system by implementing three levels of the 5C architecture used in CPS modeling and uses well-known machine learning algorithms to predict future user actions. The simulation demonstrates how users will interact with the smart home system to make more efficient use of resources. The authors also present results from analyzing real-world user data to validate the accuracy of prediction of user actions. This research illustrates the benefits of considering CPS principles when designing a home autonomous system that reliably predicts a user's needs.

scholarly journals Multilevel Simulation Methodology for FMECA Study Applied to a Complex Cyber-Physical System

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1736
Author(s):  
Davide Piumatti ◽  
Jacopo Sini ◽  
Stefano Borlo ◽  
Matteo Sonza Reorda ◽  
Radu Bojoi ◽  
...  
Keyword(s):  
Complex Systems ◽  
Physical System ◽  
Electrical Power ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Test Case ◽  
Physical Systems ◽  
Failure Classification ◽  
High Level ◽  
Criticality Analysis

Complex systems are composed of numerous interconnected subsystems, each designed to perform specific functions. The different subsystems use many technological items that work together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed of different mechanical actuators driven by electrical power devices and monitored by sensors. Several approaches are available for designing and validating complex systems, and among them, behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of faults on them and how failures in subsystems can propagate through the overall system. In this paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis (FMECA) aimed at identifying the critical faults and assessing their effects on the overall system. The end goal is to analyze how a fault affecting a single subsystem possibly propagates through the whole cyber-physical system, considering also the embedded software and the mechanical elements. In particular, our approach allows the analysis of the propagation through the whole system (working at high level) of a fault injected at low level. This paper provides a solution to automate the FMECA process (until now mainly performed manually) for complex cyber-physical systems. It improves the failure classification effectiveness: considering our test case, it reduced the number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical system architecture. The proposed approach has been tested on a real cyber-physical system in charge of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness.

scholarly journals Cyber-Physical System Modeling Using a Case Study

2018 ◽  
pp. 240-240
Author(s):  
Sara Mallah ◽  
Khalid Kouiss ◽  
Oualid Kamach ◽  
Laurent Deshayes
Keyword(s):  
Physical System ◽  
System Modeling ◽  
Cyber Physical System
Sign in / Sign up

Export Citation Format

Share Document