НЕЙРОСЕТЕВАЯ СИСТЕМА УПРАВЛЕНИЯ ВАКУУМНЫМ ДЕАЭРАТОРОМ ВД-400

The article considers the algorithms, applied in program realization of a neural network control system of concentration of oxygen of deaerated water. The analysis of the VD-400vacuum deaerator as the object of control is carried out. Control and perturbation actions, as well as adjustable parameters of VD-400 are revealed. The special attention is paid to the software, creating models of the feedforward multilayered neural networks with live training. Interfaces of training and modeling are shown. The general scheme of control of the VD-400 vacuum deaerator is presented.