Steel pickling processes are very important for steelmaking production quality. Pickling process is based on chemical reaction of acidic pickling solution with scale impurities on steel strip surface. In sulfuric acid pickling process together with scale removal. The partial dissolving of steel surface takes place because of sulfuric acid attack takes place.

The paper covers the methods and approaches of intelligent process control of pickling cold rolled steel strip with elements of comparator defect identification, based on the use of radialbasis (RBF) networks with Gaussian activation functions (GRB). The authors offer a criterion for assessing the quality of the process of etching the residual defects of the strip at the exit from the Ilyunin O.O., Gakhov R.P., Shamraev A.A. Neuro-fuzzy control of continious steel strip pickling // р а «На р а ». р я «И р а ».-. , № , 2016. 53 Ы INFORMATION TECHNOLOGIES Series ТЧsЭКХХКЭТШЧ. TСО СвЩОrsЮrПКМО ШП ЭСО ЩrШМОss ЩКrКЦОЭОrs' МСКЧРО ШП ЭСО ОЭМСТЧР sШХЮЭТШЧ КЧН MISO-model stabilization of process parameters in an optimal area for cost criteria are presented. The method of fuzzy color identification of defects on the steel strip by luminance component segmentation and positioning, and the approach to the construction of a fuzzy regulator of pressure in the nozzles of the hydraulic unit prior irrigation strip defects are offered. To study the process and the synthesis of the classifier and controller the authors used the data obtained in the course of the experiment in the production process.