Methods and Means of Applying Ontological Models in the Program Systems Lifecycle of Flight Control
Year: 2025
Type: article
Abstract: The article is devoted to the development of methods and tools for using ontology in the life cycle processes of flight control program systems, which are mission-critical systems. For a variety of mission-critical system classes, the task of developing methods for verifying these systems for compliance with the specified requirements within the subject domain and analyzing risks and hazards throughout their life cycle is relevant. Compliance assessment is typically performed by evaluating the overall quality level of flight control software components during the testing phase. To comprehensively analyze the compliance of system attributes with the specified requirements, it is necessary to examine and structure a significant number of objects and functions. To address the problem of systematization within the subject domain, it is proposed to build a formal conceptual model of the system, based on which a set of objects, basic functions, and methods for their implementation can be technologically formed. The problem of enhancing the safety of objects controlled by automated flight control systems remains constantly relevant. One way to achieve this goal is to ensure the high-quality and reliable operation of flight control program systems. This is particularly important during the operation of the admission control subsystem, which must implement control algorithms established for each type of aircraft. In case of incorrect assessment of piloting performance and equipment operation, there is a risk of allowing further flights for an unprepared crew or an aircraft with defective equipment. These factors may lead to an aviation incident, directly affecting human safety and the integrity of the aircraft. A solution to this problem is the effective application of an ontological model of flight control program system components throughout the life cycle of these systems. The developed ontological model will be used to construct a mathematical framework for representing ontology functions (tasks) in the form of automaton models. These models will be applied to solving and computing tasks of a similar type during life cycle processes, including concept creation, requirements analysis, programming, and exhaustive testing of multiple program components that implement flight control tasks. The article analyzes recent research and publications demonstrating the effectiveness of using ontologies for decision-making processes in the context of ambiguous problem situations. For flight control SW, the apparatus of ontological research can be effectively utilized, as the primary task of the SW is to determine whether the controlled object remains "within tolerance" (normal mode) or "beyond tolerance." The conducted research includes: 1) performing a domain analysis of the application area; 2) developing an ontology for flight control software, which systematizes and structures knowledge regarding concepts and objects of the subject domain; 3) defining ontology interpretation functions, as well as specifying criteria and constraints for decision-making tasks in mission-critical systems. Further research has been carried out to apply automata theory for programming control algorithms and constructing test data sets for testing the implemented software components. Based on this research, a method for programming automaton-based control models was developed, along with an example of typical program construction using programming templates. The conclusions state that the developed ontological model and its interpretation functions can be applied throughout the lifecycle of various classes of control program systems, as any control information system is characterized by the presence of a controlled object monitored by a set of parameters measured using measuring instruments. Further research is proposed in the direction of automating the creation of program components for processing parametric flight information, which requires leveraging the intelligent capabilities of artificial intelligence.
Source: Science-based technologies
Authors: Igor Raichev, Nataliia Denisenko
Institution: National University "Kyiv Aviation Institute"
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412553768