Zobrazeno 1 - 10
of 293
pro vyhledávání: '"Pyrkin, Anton"'
The article investigates an algorithm for identifying an unknown constant parameter for a scalar regression model using a nonlinear operator that allows us to obtain a new regression equation (with an expanded number of unknown parameters) for which
Externí odkaz:
http://arxiv.org/abs/2305.16359
The article is devoted to the problem of synthesis of observers of state variables for linear stationary objects operating under conditions of noise or disturbances in the measurement channel. The paper considers a fully observable linear stationary
Externí odkaz:
http://arxiv.org/abs/2305.15496
In this paper we provide the first solution to the challenging problem of designing a globally exponentially convergent estimator for the parameters of the standard model of a continuous stirred tank reactor. Because of the presence of non-separable
Externí odkaz:
http://arxiv.org/abs/2302.05731
In this paper we are interested in the problem of adaptive state observation of linear time-varying (LTV) systems where the system and the input matrices depend on unknown time-varying parameters. It is assumed that these parameters satisfy some know
Externí odkaz:
http://arxiv.org/abs/2112.05497
This paper considers the problem of frequency estimation for a multi-sinusoidal signal consisting of n sinuses in finite-time. The parameterization approach based on applying delay operators to a measurable signal is used. The result is the nth order
Externí odkaz:
http://arxiv.org/abs/2009.06400
Autor:
Pyrkin, Anton, Bobtsov, Alexey, Vedyakov, Alexey, Ortega, Romeo, Vediakova, Anastasiia, Sinetova, Madina
In this paper we address the problems of flux and speed observer design for voltage-fed induction motors with unknown rotor resistance and load torque. The only measured signals are stator current and control voltage. Invoking the recently reported D
Externí odkaz:
http://arxiv.org/abs/2009.00966
In this paper we propose a solution to the problem of parameter estimation of nonlinearly parameterized regressions--continuous or discrete time--and apply it for system identification and adaptive control. We restrict our attention to parameterizati
Externí odkaz:
http://arxiv.org/abs/1910.08016
Autor:
Ortega, Romeo, Aranovskiy, Stanislav, Pyrkin, Anton A., Astolfi, Alessandro, Bobtsov, Alexey A.
We present some new results on the dynamic regressor extension and mixing parameter estimators for linear regression models recently proposed in the literature. This technique has proven instrumental in the solution of several open problems in system
Externí odkaz:
http://arxiv.org/abs/1908.05125
Autor:
Zakharov, Dmitrii N. *, Bodrov, Kirill Yu *, Zhivitskii, Andrei Yu. *, Rodionova, Alisa D. *, Golubev, Anton K. *, Borisov, Oleg I. *, Pyrkin, Anton A. *, Zhang, Botao
Publikováno v:
In IFAC PapersOnLine 2023 56(2):2140-2145
Autor:
Sivtsov, Vladimir, Ramos, Alexander, Shavetov, Sergei, Zhivitskii, Andrei, Borisov, Oleg I., Pyrkin, Anton A.
Publikováno v:
In IFAC PapersOnLine 2023 56(2):4364-4367