Article

Article title SIMULATION MODELING OF MAKING DECISIONS IN AUTOMATIC OPTIMIZATION SYSTEMS
Authors V.I. Finaev, I.V. Pushnina, А.А. Pushnina
Section SECTION I. AUTOMATION AND CONTROL
Month, Year 05, 2016 @en
Index UDC 581.5:681.3
DOI
Abstract The purpose of this paper is algorithmization of automatic optimization under uncertainty procedures in solving the problems of extreme control of technological processes and manufactures. A short overview of the well-known methods of modeling and solving problems of automatic optimization with the control object and random disturbances known models is given in this paper to achieve this purpose. A short overview of papers in which the automatic optimization problems are solved under uncertainty is made. It is concluded that expert estimates of the model parameters should be used in conditions of uncertainty and fuzzy model of control object. Expert estimates of the model’s parameters are tested according to methods of simulation modeling. The urgency of the decision-making models’ application and the application of the simulation modeling for synthesis of the automatic optimization system, which maintains the optimal functioning parameters of the control object, is justified. A simulation model of the automatic optimization system is developed and the simulation modeling problems are identified. Meaningful description of the automatic optimization system functioning and functioning of the statistical sequential algorithm of searching control decisions are given. Estimation of accuracy of the trial control bias random search can be obtained using the normal or binomial criterion. A flowchart of the automatic optimization system with normal criteria simulation model is developed. The algorithm of the simulation model of the consistent criteria for correction of the automatic optimization system parameters is developed. The algorithm of situational model, applying of which makes stable the automatic optimization system to disturbances, acting on the control object, is developed. The difference between situational model is the application of experts’ knowledge to set the reference situations and control solutions, corresponding to them. View of the main program dialog box for the study of automatic optimization system functioning is shown.

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Keywords Control; automatic optimization; uncertainty; making decisions; modeling; algorithmization; simulation; software application
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