A situational model of identification of a state of a complex technological system under conditions of uncertainty is proposed based on a structural and parametric description of the system and agent technologies. The methodology of developing a self-learning intelligent agent capable of identifying the current situation with incomplete and fuzzy information and making adequate decisions on its normalization in real time in the management of a processing plant's technological system is described.