Development of smart technology for complex objects prediction and control on the basis of a distributed control system and an artificial immune systems approach

Abstract

This paper is an extension of work originally presented in 2018 Global Smart Industry Conference (GloSIC). Researches are devoted to the development of Smart technology for complex objects control and prediction on the basis of a distributed Honeywell DCS control system of the TengizChevroil enterprise using the example of a technological process of medium pressure gas cleaning. The article describes how on the basis of the multi-algorithm approach there was developed a modified algorithm based on modern artificial intelligence methods in order to select informative features (principal component method, Random Forest algorithm, particle swarm algorithm) and artificial immune systems (clonal selection) solving the image recognition problem and predicting the state of a complex control object. There was conducted a comparative analysis of the simulation results using the example of real production data (daily data of sensors from an average pressure absorber).