Abstract
Purposes. The modern automatic control systems represent the complexes of interacting technical devices and elements which operate based on different physical principles. Resolution of many challenging scientific and technical tasks can be simplified by using the multi-cascade fuzzy systems. Synthesis of individual modules of these complex control systems will be associated with a range of related time-consuming tasks. The approach for tuning the fuzzification blocks of fuzzy multi-cascade controllers proposed will make it possible to simplify a process of modeling this class of systems targeted at resolution of multi-objective control tasks.
Methods and approaches. Synthesis and implementation of the intelligent control system is based on integral and differential calculus elements, basic provisions of automatic control theory and standard control procedures implemented using fuzzy logic unit.
Findings: involves study and implementation of complex control laws for automation systems, which will essentially extend the intellectual opportunities while resolution of multi-objective and multifactor problems, as well as improve universality of these systems for the entire class of complex control objects. The approach for tuning the parameters of fuzzy multi-cascade systems proposed will, at the same time, reduce the efforts while the synthesis of control actions, as well as reduce the structural and algorithmic complexity of these modules with increasing the intellectual properties of automation systems as a whole.
Originality/Value: involves formulation of mathematical description of a complex multi-cascade control system considering internal and external factors, and study of different models both complex and simple multi-cascade automatic control systems, as well as implementation of multi-cascade system modeling methods taking into account all the special features of functioning of a process object.
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The research is funded from Komsomolsk-na-Amure State University Competitiveness Enhancement Program grant, Project Number R-113/NIS2019.
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Cherniy, S.P., Buzikayeva, A.V., Susdorf, V.I., Vasilchenko, S.A. (2021). Algorithm of Fuzzy Controller Membership Function Allocation at Fuzzification Stage. In: Shakirova, O.G., Bashkov, O.V., Khusainov, A.A. (eds) Current Problems and Ways of Industry Development: Equipment and Technologies. Lecture Notes in Networks and Systems, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-030-69421-0_13
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