Abstract
In a market economy, there is a critical need to introduce optimal control systems for technological processes in industries like non-ferrous and ferrous metallurgy, the chemical industry, and petrochemicals. These systems can help use mineral resources more efficiently, save energy, reduce environmental impact, and increase production efficiency. The active development and implementation of such optimal control systems began in the 1960s-1980s, but significant automated systems have not yet been widely adopted. This is due to the extreme complexity of the physical and chemical phenomena in modern industrial processes, which makes it difficult to create adequate mathematical models. Recently, there has been a trend toward using modern intelligent technologies that can leverage the knowledge, experience, and intuition of experts. The use of artificial intelligence methods in designing optimal control systems has significantly simplified their development, improved control models, and increased efficiency. Therefore, the urgent task is to develop and implement intelligent control models (algorithms) for various technological processes, including those in the phosphorus industry. The text proposes using new intelligent algorithms to control a complex technological process - the purification of phosphorus from arsenic and organics at the Novodzhambyl Phosphorus Plant (NDPP).