Chemical Technology, Control and Management


Paper formulated the problem of increasing the quality of identification for casual time series (CTS), representing non-stationary objects in multicontour control systems on the basis of effective search of global and local extremums when parameters of target optimization function are rational. The new approach is offered to optimization of search by consideration statistical and dynamic characteristics of CTS as specimen of population generation, and by reflection of coordinate points set in space of evolution toward optimal values of target function. The modified genetic algorithm (GA) is developed on the basis of overlapping, generalization of opportunities and use of properties of genetic operators for evolutionary modeling. Procedures are entered for statistical selection of search points population, exception "unsuccessful" descendants, change of specimen generations on the basis of elimination and replacement unpromising specimen. Efficiency of the program complex to CTS identification is investigated on the basis of mechanisms to adjustment of parameters by recurrent dependences, traditional and modified GA.

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