Knoll, C.; Fiedler, J.; Ecklebe, S. Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory. Machines2024, 12, 181.
Knoll, C.; Fiedler, J.; Ecklebe, S. Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory. Machines 2024, 12, 181.
Knoll, C.; Fiedler, J.; Ecklebe, S. Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory. Machines2024, 12, 181.
Knoll, C.; Fiedler, J.; Ecklebe, S. Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory. Machines 2024, 12, 181.
Abstract
This paper is motivated by three main assumptions: (1) The currently dominant forms of knowledge representation (natural language text, formulas, graphics) are suboptimal to facilitate knowledge transfer between control engineering sub-fields and into potential application domains. (2) Formal knowledge representation (in general) is a promising supplementary approach, but (3) the established technologies so far have failed to be significantly adopted for formal representation of control engineering knowledge. Thus, after briefly reviewing existing representation methods, we introduce our own approach: The Python based imperative representation of knowledge (PyIRK) and its application to formulate the Ontology of Control Systems Engineering (OCSE). One of its main features is the possibility to represent the actual content of definitions and theorems as nodes and edges of a knowledge graph, which is demonstrated by selected elements from Lyapunov theory. While the approach is still experimental, the formalization already allows to apply methods of automated quality assurance and a semantic search mechanism. The current feature set of the framework is demonstrated on various examples before directions for further developments are discussed.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
