Journals
Books
Articles by keyword ПИД-регулятор
Choice of RNS Bases for Realization of Modular PID-Neurocontroller
N.I. Chervyakov, T.A. Rudakova, A.A. Yevdokimov, V.F. Lubencov, M.A. Ospishev
Modular PID-Neurocontroller with the Expanded Functionalities
N. I. Chervyakov, T. A. Rudakova, A. A. Yevdokimov, V. F. Lubencov, M. A Ospishhev
Adaptive control device synthesis of active magnetic suspension for high-energy rotor machines
Т.A. Izosimova - Post-graduate Student, Department «Еlectronics and information and measurement technology», Kazan National Research Technical University named after A.N. Tupolev; Senior Lecturer, Department «Management and informatics in technical systems», Cheboksary Polytechnic Institute «Moscow State Engineering University (MSEU)» (Cheboksary). E-mail: ta_iz@mail.ru
Yu.K. Evdokimov - Dr.Sc. (Eng), Professor, Honored Worker of Science of the Republic of Tatarstan, Head of the Department «Еlectronics and information and measurement technology», Kazan National Research Technical University named after A.N. Tupolev. E-mail: evdokimov1@mail.ru
Adaptive control of the dynamic behavior of the rotor in active magnetic bearings
Т. A. Izosimova - Post-graduate Student. E-mail: ta_iz@mail.ru
Yu. K. Evdokimov - Dr.Sc. (Eng.), Professor, Head of Department. E-mail: evdokimov@tre.kstu-kai.ru
Model of a neural network adaptive system for a digital control loop of an electric drive

O.V. Nepomnyashchiy, A.V. Tarasov, Yu.V. Krasnobaev, V.N. Khaidukova, D.O. Nepomnyashchiy

Siberian Federal University (Krasnoyarsk Russia)

Application of intelligent technologies for modeling of controlled switching systems

D.Y. Openkin1, S.V. Chernomordov2

1,2 Yelets Bunin Yelets State University (Yelets, Russia) 

Modeling firefighting ladder stabilization system

V.A. Trudonoshin1, V.A. Ovchinnikov2, A.S. Domnikoff3

1 Bauman Moscow State Technical University (Moscow, Russia),

2 Laduga LLC (Togliatti, Russia),

3 National Research Nuclear University "MEPhI" (NIAU MEPhI) (Obninsk, Russia)

Application of intelligent technologies for modeling of controlled switching systems

D.Y. Openkin1, S.V. Chernomordov2

1,2 Yelets Bunin Yelets State University (Yelets, Russia)
 

Model of the adaptive system based on an artificial neural network for digital electric motor control

O.V. Nepomnyashchiy1, I.A. Rusak2, N.Y. Sirotinina3, A.A. Kopytov4, V.N. Khaidukova5

1–5 Siberian Federal University (Krasnoyarsk, Russia)