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System identification

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The article was published on 1988-01-01 and is currently open access. It has received 5375 citations till now. The article focuses on the topics: System identification.

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Journal ArticleDOI

Non-linear system identification using closed-loop data with no external excitation: The case of a lean combustion chamber

TL;DR: In this paper, the authors deal with the analysis of a set of measurements collected on a lean premixed combustion process operating in a limit cycle and show that, despite the paucity of information available, a grey box nonlinear model can be estimated.
Book ChapterDOI

Fuzzy identification from a grey box modeling point of view

TL;DR: The design of mathematical models of complex real-world systems is essential in many fields of science and engineering to explain the behavior of the underlying system and for prediction and control purposes.
Journal ArticleDOI

Maximum-likelihood bearing estimation with partly calibrated arrays in spatially correlated noise fields

TL;DR: The ML estimator introduced in this paper, and referred to as MLE, is shown to be asymptotically equivalent to a recently proposed subspace-based bearing estimator called UNCLE and rederived herein by a much simpler approach than in the original work.
Journal ArticleDOI

Approaches to robust process identification: A review and tutorial of probabilistic methods

TL;DR: A general introduction to the probabilistic methods for robust identification is provided, the main steps involved in the development of models are illustrated, and the related literature is reviewed.

A Fast Recursive Total Least Squares Algorithm for

TL;DR: This paper develops a new fast recursive total least squares (N-RTLS) algorithm to recursively compute the total least square solution for adaptive infinite-impulse-response (IIR) filtering and the global convergence of the new algorithm is studied.