The article describes a technique of developing neural network models of controllers for controlling a technical object, approximating the relationship between the control action and the deviation of the state of the object from the setting action, its speed and acceleration. The application of a technique for controlling the temperature of a water bath water heater is considered. The technical object is described by a second-order differential equation and has a smooth monotonic behavior.

Keywords: technical object, water bath, water heater, neural regulator, control, object behavior, model, neural network, training set, perceptron