Identification of models of nonlinear dynamic processes in mining on the basis of Volterra nuclei

Kryvyi Rih National University, Department of Automation, Computer Sciences and Technology, 11 Matusevycha St., 50027 Kryvyi Rih, Ukraine

^* Corresponding author: nmorkun@knu.edu.ua

Abstract

Solving the problem of improving efficiency of technological processes of mineral concentration is one of the essential for providing sustainability of mining enterprises. Currently, special attention is paid to optimization of technological processes in concentration of useful minerals. This approach calls for availability of high-quality data on the process, formation of corresponding databases and their subsequent processing to build adequate and efficient mathematical models of processes and systems. In order to improve quality of mathematical description of forming fractional characteristics of ore through applying technological aggregates in concentration, the authors suggest using power Volterra series that provide characteristics of a controlled object (its condition) as a sequence of multidimensional weight functions invariant to the type of an input signal – Volterra nuclei. Application of Volterra structures enables decreasing the modelling error to 0.039 under the root-mean-square error of 0.0594.