TY - JOUR

T1 - Frequency estimation of a sinusoidal signal with time-varying amplitude and phase

AU - Vedyakov, Alexey A.

AU - Vediakova, Anastasiia O.

AU - Bobtsov, Alexey A.

AU - Pyrkin, Anton A.

AU - Kakanov, Mikhail A.

N1 - Conference code: 17

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - a globally convergent estimator

KW - continuous-time estimation

KW - online frequency estimation

UR - http://www.scopus.com/inward/record.url?scp=85058226771&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2018.11.501

DO - 10.1016/j.ifacol.2018.11.501

M3 - Conference article

AN - SCOPUS:85058226771

VL - 51

SP - 663

EP - 668

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 32

T2 - 17th IFAC Technical-Committee-on-Optimal-Control (TC 2.4) Workshop on Control Applications of Optimization (CAO)

Y2 - 15 October 2018 through 19 December 2018

ER -