APPLICATION OF SOFT SITUATIONAL-COGNITIVE MODELS FOR INTELLIGENT CONTROL OF COMPLEX SYSTEMS AND PROCESSES
Abstract
Currently, it is in demand to design methods and technologies for intelligent control of complex systems and processes that take into account situational awareness of problems, various control strategies and scenarios for achieving target situations in conditions of uncertainty. Models and methods based on fuzzy situational and fuzzy cognitive approaches take into account the specifics of situational awareness when controlling such systems and processes. The limitations of fuzzy situational models in controlling complex systems and processes under conditions of uncertainty are: the difficulty of accounting for the mutual influence of situational features due to the ambiguity of transitions from one fuzzy situation to another; the difficulty of assessing the simultaneous impact of several control decisions on various interdependent situational features; insufficient consideration of the time factor and duration of the impact of situational decisions on situational features; the difficulty of modeling scenario dynamics taking into account various strategies. Due to this, the best sequence of control decisions is formed, depending on the chosen strategy, and the time of their application is justified. The paper discusses the application of a new proposed variety of Soft Situational-Cognitive Models for intelligent control of turbocharger air installations. The results of the comparative assessment make it possible to substantiate the improvement of the quality of intelligent control and the efficiency of turbocharger air installations in conditions of uncertainty using the proposed model for various control strategies and scenarios for achieving target situations.
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