The Experts below are selected from a list of 18297 Experts worldwide ranked by ideXlab platform

Stanislav Aranovskiy - One of the best experts on this subject based on the ideXlab platform.

  • Online Estimation of time-varying frequency of a Sinusoidal Signal
    2019
    Co-Authors: Le Tuan, Marina Korotina, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin
    Abstract:

    We consider the problem of estimation of a (linearly) time-varying frequency of a Sinusoidal Signal with unknown phase and magnitude. Such a problem may arise in control design for optical telescopes that makes it interesting from the practical point of view. The existing methods typically use unbounded functions of time that, being multiplying by the input Signal, may yield significant noise amplification and poor estimation performance. In contrast, we present a novel approach to the estimation of the linearly varying frequency based on iterative filtering yielding simple linear regression model with a scalar parameter. Illustrative numerical simulations support the theoretical results. We also present a comparison with other known methods.

  • a globally convergent frequency estimator of a Sinusoidal Signal with a time varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin, Anastasiia O. Vediakova
    Abstract:

    Abstract The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently presented dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the suggested frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A globally convergent frequency estimator of a Sinusoidal Signal with a time-varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Stanislav Aranovskiy
    Abstract:

    The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently proposed dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the proposed frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A method for increasing the rate of parametric convergence in the problem of identification of the Sinusoidal Signal parameters
    Automation and Remote Control, 2017
    Co-Authors: Jian Wang, Alexey Bobtsov, Stanislav Aranovskiy, P. A. Gritsenko, Anton Pyrkin
    Abstract:

    The problem of identification of the Sinusoidal Signal parameters is very popular in the modern theory and practice of the automatic control. However, the problem of quality of estimation related with the increase in the rate of parametric identification is studied weakly until now. At the same time, the requirements on the quality of processes at realization of the up-to-date systems represent one of the key criteria for selecting one or another approach. A new method for estimation of the Sinusoidal Signal parameters enabling an increase in the rate of parametric identification was proposed. Consideration was given to a Signal representing a sum of two sinusoids which can be easily extended to a more general case.

  • ALCOSP - The New Algorithm of Sinusoidal Signal Frequency Estimation
    IFAC Proceedings Volumes, 2013
    Co-Authors: Alexey Bobtsov, Nikolay Nikolaev, Olga Slita, Alexander S. Borgul, Stanislav Aranovskiy
    Abstract:

    In this paper we consider the new estimation algorithm of the measured Sinusoidal Signal frequency. Unlike most of known similar methods, the proposed algorithm provides the opportunity of partial rejection of unaccounted disturbances presenting in the channel of useful Signal measurement. The latter in its turn allows obtaining more accurate estimation of unknown frequency of the measured Sinusoidal Signal.

Alexey Bobtsov - One of the best experts on this subject based on the ideXlab platform.

  • Online Estimation of time-varying frequency of a Sinusoidal Signal
    2019
    Co-Authors: Le Tuan, Marina Korotina, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin
    Abstract:

    We consider the problem of estimation of a (linearly) time-varying frequency of a Sinusoidal Signal with unknown phase and magnitude. Such a problem may arise in control design for optical telescopes that makes it interesting from the practical point of view. The existing methods typically use unbounded functions of time that, being multiplying by the input Signal, may yield significant noise amplification and poor estimation performance. In contrast, we present a novel approach to the estimation of the linearly varying frequency based on iterative filtering yielding simple linear regression model with a scalar parameter. Illustrative numerical simulations support the theoretical results. We also present a comparison with other known methods.

  • frequency estimation of a Sinusoidal Signal with time varying amplitude and phase
    IFAC-PapersOnLine, 2018
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Mikhail A Kakanov
    Abstract:

    Abstract This paper is devoted to frequency estimation of a non-stationary Sinusoidal Signal. The amplitude is supposed to be a known function within a constant factor, the phase should be known. Example of such problem statement is sensorless angular velocity estimation for permanent magnet synchronous motors. On the first step by reparametrization, a third order linear regression model is obtained. On the next step, an estimation algorithm is constructed based on a standard gradient approach. The frequency estimate can be computed from one of the model parameters using inverse trigonometric functions. To improve estimates quality for noisy measurements we propose a new identification method, which can be tuned to attenuate the noise influence. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input Signal. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.

  • a globally convergent frequency estimator of a Sinusoidal Signal with a time varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin, Anastasiia O. Vediakova
    Abstract:

    Abstract The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently presented dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the suggested frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A globally convergent frequency estimator of a Sinusoidal Signal with a time-varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Stanislav Aranovskiy
    Abstract:

    The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently proposed dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the proposed frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A method for increasing the rate of parametric convergence in the problem of identification of the Sinusoidal Signal parameters
    Automation and Remote Control, 2017
    Co-Authors: Jian Wang, Alexey Bobtsov, Stanislav Aranovskiy, P. A. Gritsenko, Anton Pyrkin
    Abstract:

    The problem of identification of the Sinusoidal Signal parameters is very popular in the modern theory and practice of the automatic control. However, the problem of quality of estimation related with the increase in the rate of parametric identification is studied weakly until now. At the same time, the requirements on the quality of processes at realization of the up-to-date systems represent one of the key criteria for selecting one or another approach. A new method for estimation of the Sinusoidal Signal parameters enabling an increase in the rate of parametric identification was proposed. Consideration was given to a Signal representing a sum of two sinusoids which can be easily extended to a more general case.

Anton Pyrkin - One of the best experts on this subject based on the ideXlab platform.

  • Online Estimation of time-varying frequency of a Sinusoidal Signal
    2019
    Co-Authors: Le Tuan, Marina Korotina, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin
    Abstract:

    We consider the problem of estimation of a (linearly) time-varying frequency of a Sinusoidal Signal with unknown phase and magnitude. Such a problem may arise in control design for optical telescopes that makes it interesting from the practical point of view. The existing methods typically use unbounded functions of time that, being multiplying by the input Signal, may yield significant noise amplification and poor estimation performance. In contrast, we present a novel approach to the estimation of the linearly varying frequency based on iterative filtering yielding simple linear regression model with a scalar parameter. Illustrative numerical simulations support the theoretical results. We also present a comparison with other known methods.

  • frequency estimation of a Sinusoidal Signal with time varying amplitude and phase
    IFAC-PapersOnLine, 2018
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Mikhail A Kakanov
    Abstract:

    Abstract This paper is devoted to frequency estimation of a non-stationary Sinusoidal Signal. The amplitude is supposed to be a known function within a constant factor, the phase should be known. Example of such problem statement is sensorless angular velocity estimation for permanent magnet synchronous motors. On the first step by reparametrization, a third order linear regression model is obtained. On the next step, an estimation algorithm is constructed based on a standard gradient approach. The frequency estimate can be computed from one of the model parameters using inverse trigonometric functions. To improve estimates quality for noisy measurements we propose a new identification method, which can be tuned to attenuate the noise influence. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input Signal. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.

  • a globally convergent frequency estimator of a Sinusoidal Signal with a time varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin, Anastasiia O. Vediakova
    Abstract:

    Abstract The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently presented dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the suggested frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A globally convergent frequency estimator of a Sinusoidal Signal with a time-varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Stanislav Aranovskiy
    Abstract:

    The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently proposed dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the proposed frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A method for increasing the rate of parametric convergence in the problem of identification of the Sinusoidal Signal parameters
    Automation and Remote Control, 2017
    Co-Authors: Jian Wang, Alexey Bobtsov, Stanislav Aranovskiy, P. A. Gritsenko, Anton Pyrkin
    Abstract:

    The problem of identification of the Sinusoidal Signal parameters is very popular in the modern theory and practice of the automatic control. However, the problem of quality of estimation related with the increase in the rate of parametric identification is studied weakly until now. At the same time, the requirements on the quality of processes at realization of the up-to-date systems represent one of the key criteria for selecting one or another approach. A new method for estimation of the Sinusoidal Signal parameters enabling an increase in the rate of parametric identification was proposed. Consideration was given to a Signal representing a sum of two sinusoids which can be easily extended to a more general case.

Alexey A. Vedyakov - One of the best experts on this subject based on the ideXlab platform.

  • frequency estimation of a Sinusoidal Signal with time varying amplitude and phase
    IFAC-PapersOnLine, 2018
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Mikhail A Kakanov
    Abstract:

    Abstract This paper is devoted to frequency estimation of a non-stationary Sinusoidal Signal. The amplitude is supposed to be a known function within a constant factor, the phase should be known. Example of such problem statement is sensorless angular velocity estimation for permanent magnet synchronous motors. On the first step by reparametrization, a third order linear regression model is obtained. On the next step, an estimation algorithm is constructed based on a standard gradient approach. The frequency estimate can be computed from one of the model parameters using inverse trigonometric functions. To improve estimates quality for noisy measurements we propose a new identification method, which can be tuned to attenuate the noise influence. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input Signal. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.

  • a globally convergent frequency estimator of a Sinusoidal Signal with a time varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin, Anastasiia O. Vediakova
    Abstract:

    Abstract The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently presented dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the suggested frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A globally convergent frequency estimator of a Sinusoidal Signal with a time-varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Stanislav Aranovskiy
    Abstract:

    The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently proposed dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the proposed frequency estimator is established, and the obtained performance is illustrated with simulations.

Anastasiia O. Vediakova - One of the best experts on this subject based on the ideXlab platform.

  • frequency estimation of a Sinusoidal Signal with time varying amplitude and phase
    IFAC-PapersOnLine, 2018
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Mikhail A Kakanov
    Abstract:

    Abstract This paper is devoted to frequency estimation of a non-stationary Sinusoidal Signal. The amplitude is supposed to be a known function within a constant factor, the phase should be known. Example of such problem statement is sensorless angular velocity estimation for permanent magnet synchronous motors. On the first step by reparametrization, a third order linear regression model is obtained. On the next step, an estimation algorithm is constructed based on a standard gradient approach. The frequency estimate can be computed from one of the model parameters using inverse trigonometric functions. To improve estimates quality for noisy measurements we propose a new identification method, which can be tuned to attenuate the noise influence. It is shown that the frequency estimation error converges to zero exponentially fast. The described algorithm does not require measuring or calculating derivatives of the input Signal. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.

  • a globally convergent frequency estimator of a Sinusoidal Signal with a time varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Stanislav Aranovskiy, Anton Pyrkin, Anastasiia O. Vediakova
    Abstract:

    Abstract The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently presented dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the suggested frequency estimator is established, and the obtained performance is illustrated with simulations.

  • A globally convergent frequency estimator of a Sinusoidal Signal with a time-varying amplitude
    European Journal of Control, 2017
    Co-Authors: Alexey A. Vedyakov, Alexey Bobtsov, Anton Pyrkin, Anastasiia O. Vediakova, Stanislav Aranovskiy
    Abstract:

    The paper considers the problem of continuous-time online frequency estimation for a Sinusoidal Signal with a time-varying amplitude, where the latter is given by a known function of time multiplied by an unknown constant. To solve the problem a novel parameterization method is applied yielding linear regression with three unknown constant parameters. Next, two estimation algorithms are proposed, where the first is based on the conventional gradient approach, and a recently proposed dynamic regressor extension and mixing procedure is used for the second. Global exponential convergence of the proposed frequency estimator is established, and the obtained performance is illustrated with simulations.