Performance analysis of multi-innovation gradient type identification methods
Automatica (Journal of IFAC)
Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems
Computers & Mathematics with Applications
Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems
Automatica (Journal of IFAC)
Multi-innovation stochastic gradient algorithms for multi-input multi-output systems
Digital Signal Processing
Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systems
Computers & Mathematics with Applications
Identification of Hammerstein nonlinear ARMAX systems
Automatica (Journal of IFAC)
Hierarchical gradient-based identification of multivariable discrete-time systems
Automatica (Journal of IFAC)
Auxiliary model identification method for multirate multi-input systems based on least squares
Mathematical and Computer Modelling: An International Journal
An approach for identification of uncertain Wiener systems
Mathematical and Computer Modelling: An International Journal
Estimation of the quasi-linear viscoelastic parameters using a genetic algorithm
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Time series AR modeling with missing observations based on the polynomial transformation
Mathematical and Computer Modelling: An International Journal
Computers & Mathematics with Applications
Mathematical and Computer Modelling: An International Journal
| Hi-index | 0.98 |
Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. This paper presents a gradient based algorithm and a least squares based algorithm to estimate the fundamental frequency, the amplitudes and the phases of harmonic waves according to the voltage/current samples of a power system. Differing from the existing parameter estimation algorithms either for power quality monitoring or for harmonic compensation, the proposed algorithms are based on the hierarchical identification principle and are able to estimate the fundamental frequency, the amplitudes and the phases of harmonic waves simultaneously. In addition, the proposed algorithms are in the recursive form, which is suitable for on-line implementation. The simulation results verify the effectiveness of the proposed algorithms.