Gradient-based and least-squares-based iterative algorithms for Hammerstein systems using the hierarchical identification principle

This study derives a least-squares-based iterative algorithm and a gradient-based iterative algorithm for Hammerstein systems using the decomposition-based hierarchical identification principle. The simulation results confirm that the proposed two algorithms can give satisfactory identification accu...

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Vydáno v:	IET control theory & applications Ročník 7; číslo 2; s. 176 - 184
Hlavní autoři:	Ding, Feng, Liu, Xinggao, Chu, Jian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Stevenage The Institution of Engineering and Technology 01.01.2013 John Wiley & Sons, Inc
Témata:	Algorithms Computer simulation Control theory Convergence Decomposition decomposition‐based hierarchical identification principle fast convergence rates gradient methods gradient‐based iterative algorithm Hammerstein systems Iterative algorithms iterative methods least squares approximations Least squares method least‐squares‐based iterative algorithms nonlinear control systems parameter estimation satisfactory identification accuracies iterative methods gradient-based iterative algorithm least squares approximations satisfactory identification accuracies least-squares-based iterative algorithms nonlinear control systems parameter estimation decomposition gradient methods decomposition-based hierarchical identification principle Hammerstein systems fast convergence rates
ISSN:	1751-8644, 1751-8652
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