Currently, the development of intelligent production systems based on modern artificial intelligence methods is an urgent problem. Industrial automation has its own specific limitations in the application of artificial intelligence at the level of software and hardware implementation. The creation of a new modified endocrine-immune algorithm (EAIS) for complex objects control and diagnosing the state of equipment is a promising and relevant task. The proposed EAIS algorithm is adapted for work with industrial controllers of the Modicon series (Schneider Electric) of the IEC 61131–3 standard. The results of modeling and experiments were carried out in the Industrial Automation Lab (KBTU JSC). The developed algorithm was tested on the engineering database of the Tengizchevroil oil refinery and modeled using the Modicon M340 controller. The advantages of EAIS include the ability to be placed directly in the controller without using external servers for training. For this purpose, a user-defined functional block DFB (Derived Functional Block) is created with a modified endocrine-immune algorithm EAIS_FBD, implemented in the ST (Structured Text) language. The organization of an intellectual structural program unit (Intellectual Program Organization Unit) is proposed for placing the functional block EAIS_FBD and multiple use in the development of process control systems. Comparative analysis of the results of modeling with the support vector method, decision trees and nearest neighbors showed the superiority of EAIS.