StatusThe thesis was presented on the 9 June, 2016
Approved by NCAA on the 5 July, 2016
Abstract– 1.87 Mb / in romanian
– 2.30 Mb / in russian
6.83 Mb /
Thesis is submitted for the degree of doctor of Informatics, speciality 122.03 – Modelling, mathematical methods and software. The work is performed in the Laboratory of intelligent control systems of the Institute of system analysis and control of the Dubna University and the Laboratory of information systems in the Institute of mathematics and computer science of Academy of Sciences of Moldova.
Structure: the thesis is written in Russian and consists of introduction, 3 chapters, 3 applications, 60 figures, 8 tables, main summary, recommendations and references which include 152 items. The main text of the dissertation is set forth on 121 pages. The results of the thesis have been published in 15 scientific publications.
Area of research: intelligent control systems, emergency and unpredicted situations of control, quantum soft computing.
Goal of research: development of methods for algorithmic and software support of the process of modeling and designing of robust intelligent control systems
Scientific novelty: A new method is proposed for improving the robustness of intelligent control systems on the basis of application of quantum fuzzy inference, forming a synergetic effect of self-organization of knowledge bases in real-time
An important scientific problem is solved: the thesis proposes a design technology of quantum algorithmically cells of intelligent control systems that contributes to robustness improvement of the behavior of dynamically unstable object in unpredicted and emergency control situation.
Theoretical significance: it is shown that the proposed quantum algorithm of knowledge self-organization allows extracting hidden quantum information from classical states of knowledge bases and generating synergetic effect of self-organization in KB of robust intelligent control systems.
Practical value: the developed design method of intelligent control systems based on quantum fuzzy inference enables achieving the control objects in emergency control situations, in which classical control systems do not accomplishing goal of control.
Results implementation: The research results can be used to improve the functioning reliability of intelligent control systems in emergency and unpredicted situations.