Modelling and multi-innovation parameter identification for Hammerstein nonlinear state space systems using the filtering technique
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Publication:2808783
DOI10.1080/13873954.2016.1142455zbMath1339.93106OpenAlexW2299834062MaRDI QIDQ2808783
Publication date: 24 May 2016
Published in: Mathematical and Computer Modelling of Dynamical Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/13873954.2016.1142455
Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)
Related Items (11)
Identification of non-uniformly sampled Wiener systems with dead-zone non-linearities ⋮ Multistage for identification of Wiener time delay systems based on hierarchical gradient approach ⋮ Convergence analysis of the hierarchical least squares algorithm for bilinear-in-parameter systems ⋮ The recursive least squares identification algorithm for a class of Wiener nonlinear systems ⋮ Combined parameter and state estimation algorithms for multivariable nonlinear systems using MIMO Wiener models ⋮ Recursive least squares and multi-innovation gradient estimation algorithms for bilinear stochastic systems ⋮ Hierarchical stochastic gradient algorithm and its performance analysis for a class of bilinear-in-parameter systems ⋮ Separation identification approach for the <scp>Hammerstein‐Wiener</scp> nonlinear systems with process noise using correlation analysis ⋮ Correlation analysis-based parameter learning of Hammerstein nonlinear systems with output noise ⋮ Modelling and identification of nonlinear cascade systems with backlash input and static output nonlinearities ⋮ An online identification algorithm of unknown time-varying delay and internal multimodel control for discrete non-linear systems
Uses Software
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