No abstract

No abstract

In the scientific article the requirements for regulated energy-efficient AC electric drives of metallurgical production facilities are formulated. The main stages of development of synchronous reluctance electric drives, including the development of power units, the synthesis of the control system, the choice of mathematical apparatus, as well as the experimental study of the developed system are shown. For the mechanism of a flying shear at PJSC “Chelyabinskiy metalurgicheskiy kombinat” the use of contactless synchronous electric drive with brushless salient pole rotor is most effective, as this allows you to implement over the time of 4-6 times of the rated value and the ability to work in chemically aggressive conditions. It is shown that the task of providing the trajectory of motion can be implemented only in systems with independent control over the excitation channel and the armature. It is shown that as a mathematical description of the system, the structure of the electric drive can be used, similar to the DC drive, but the control signals are supplied from the phase current formation node. The method of experimental research shows that the synthesis of current control circuits can be performed by frequency response methods. Analysis of the experimental current waveforms showed that the separate control of the armature and excitation current is realized independently, while the specific indicators of the system were better than synchronous frequency-controlled electric drives by about 25.

This paper introduces a scalar numerical differentiator, represented as a system of nonlinear differential equations of any high order. We derive the explicit solution for this system and demonstrate that, with a suitable choice of differentiator order, the error converges to zero for polynomial signals with additive white noise. In more general cases, the error remains bounded, provided that the highest estimated derivative is also bounded. A notable advantage of this numerical differentiation method is that it does not require tuning parameters based on the specific characteristics of the signal being differentiated. We propose a discretization method for the equations that implements a cumulative smoothing algorithm for time series. This algorithm operates online, without the need for data accumulation, and it solves both interpolation and extrapolation problems without fitting any coefficients to the data.

No abstract