Imperative Formal Knowledge Representation for Control Engineering: Examples from Lyapunov Theory

Research output: Contribution to journalResearch articleContributedpeer-review


In this paper, we introduce a novel method to formally represent elements of control engineering knowledge in a suitable data structure. To this end, we first briefly review existing representation methods (RDF, OWL, Wikidata, ORKG). Based on this, 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 theorems from Lyapunov’s theory. While the approach is still experimental, the current result already allows the application of methods of automated quality assurance and a SPARQL-based semantic search mechanism. The feature set of the framework is demonstrated by various examples. The paper concludes with a discussion of the limitations and directions for further development.


Original languageEnglish
Article number181
JournalMachines : open access journal
Issue number3
Publication statusPublished - 8 Mar 2024

External IDs

ORCID /0000-0002-4911-1233/work/156338120
Mendeley 83f1c912-43ba-3206-b9b6-37e0654770ef
unpaywall 10.3390/machines12030181
Scopus 85189005221



  • Lyapunov theory, formal knowledge representation, knowledge graph, imperative knowledge representation, ontology, Lyapunov function, Python