Name
Title | ||
|---|---|---|
Guest Editorial: Introduction to the Special Issue on Resilient Control Architectures and Systems |
Abstract | ||
|---|---|---|
Modern societies depend on complex and critical infrastructures for energy, transportation, sustenance, medical care, emergency response, communications security. As computers, automation, and information technology (IT) have advanced, these technologies have been exploited to enhance the efficiency of operating the processes that make up these infrastructures. Where commonalities exist between different infrastructures or elements of a common infrastructure, such as in the electric power grid, the potential for even greater efficiencies has fueled the desire to integrate intelligent sensing and control architectures and methods over a large region. The results of this integration are the highly interconnected and interdependent control systems of today. However, as we have observed over recent decades, natural disasters, and terrorist attacks can produce failures in complex systems such as utility and transportation infrastructure the consequences of which resulting enormous losses to economy and security. To minimize the impact of these crippling events, society requires control system architectures and methods that maximize the resilience of the complex systems upon which society depends. By “resilience” we mean the capacity of a control system to maintain state awareness and to proactively maintain a safe level of operational normalcy in response to anomalies, including threats of a malicious and unexpected nature [1]. Threats are those elements that counter normalcy and destabilize control system networks, including human error and malicious human attacks, complex latencies and interdependencies. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TCYB.2014.2339951 | Cybernetics, IEEE Transactions |
Field | DocType | Volume |
Interdependence,Psychological resilience,Sustenance,Information technology,Computer security,Natural disaster,Human error,Automation,Artificial intelligence,Machine learning,Mathematics,Communications security | Journal | 44 |
Issue | ISSN | Citations |
11 | 2168-2267 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Craig G. Rieger | 1 | 1 | 0.35 |
| David H. Scheidt | 2 | 1 | 0.35 |
| William D. Smart | 3 | 226 | 26.50 |