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.

Original languageEnglish
Pages (from-to)663-668
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number32
DOIs
StatePublished - 2018
Event17th IFAC Technical-Committee-on-Optimal-Control (TC 2.4) Workshop on Control Applications of Optimization (CAO) - Россия, Yekaterinburg, Russian Federation
Duration: 15 Oct 201819 Dec 2018
Conference number: 17
https://www.ipu.ru/node/43678

    Research areas

  • a globally convergent estimator, continuous-time estimation, online frequency estimation

    Scopus subject areas

  • Control and Systems Engineering

ID: 76547968