Modeling and analyzing technical systems as complex networks: Detecting inverse response

”Complex networks” is the term for a research area where complex systems are modeled by a graph to analyze their structural behavior. They are mostly used in the areas of social sciences, biology and physics. For example, complex networks are a proper method to describe and analyze the non-trivial characteristics depending on the interconnection in a society or between human organs. In the context of computational intelligence, this paper introduces an idea to transfer the methods of the area of complex networks to technical systems, and, fur-thermore, enhance them to permit analyzing dynamic behavior. As a basis for the method transfer a transfer-function-based graph is presented which allows modeling technical systems in the same way as complex networks. The potential to detect dynamical behavior, in addition to structural behavior, is demonstrated by a new algorithm that detects inverse response in interconnected systems based on methods of complex networks. The introduced algorithm provides a qualitative answer if inverse response behavior is possible between a pair of input and output of a system. Finally, two case studies are used to demonstrate the algorithm.