Abstract :
Summary form only given. Today´s more reliable communication technology, together with the availability of higher computational power, have paved the way for introduction of more advanced automation systems based on distributed intelligence and multi-agent technology. However, abundance of control and measurement data, while making these systems more powerful than the traditional ones, can act as their biggest vulnerability. In a web of interconnected components functioning within an automation framework, potential impact of malfunction in a single component, either through internal failure or external damage/intrusion, may lead to detrimental side-effects spread across the whole underlying system. The potentially large number of devices, along with their inherent interrelations and interdependencies, may in many instances hinder the ability of human operators to interpret events, identify the scope of impact and take remedial actions if necessary. Through utilization of the concepts of graph-theoretic fuzzy cognitive maps and expert systems, this proposal puts forth a solution that is able to reveal weak links and vulnerabilities of an automation system, should it become exposed to partial internal failure or external damage.
Keywords :
cognitive systems; expert systems; fuzzy systems; graph theory; multi-agent systems; power system control; distributed intelligence; expert systems; graph theoretic fuzzy cognitive maps; integrity assessment scheme; multi-agent technology; situational awareness; utility automation systems; Automation; Availability; Communications technology; Computer science; Educational institutions; Reliability engineering;