Journal
AUTOMATION AND REMOTE CONTROL
Volume 84, Issue 7, Pages 788-796Publisher
MAIK NAUKA/INTERPERIODICA/SPRINGER
DOI: 10.1134/S0005117923070044
Keywords
soft sensor; model predictive control (MPC); identification; machine learning; clustering methods; associative search
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The article proposes a method for creating soft sensors using identification models obtained by associative search algorithm. The method constructs an approximating hypersurface of the space of input vectors and their corresponding one-dimensional outputs at each time instant. Case studies are presented to evaluate the advantages of the author's method over traditional approaches.
The article proposes a method for creating soft sensors using identification models obtained by associative search algorithm. The method consists in constructing an approximating hypersurface of the space of input vectors and their corresponding one-dimensional outputs at each time instant. Case studies are presented and the advantages of the author's method over traditional approaches are evaluated are revealed.
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