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In the process of parameters identification in the linear fitting, replace the Euclidean distance by the module and angle of vector as the optimal object.
The paper deals with tracking problem for single-input single-output linear systems with unstable zero dynamics under parametric and signal uncertainty of control plant and reference model within the framework of the sliding mode techniques for feedback design, state observation and parameters identification in real time.
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An algorithm for parameter identification in continuous time is presented.
Operational modal analysis is the primary tool for modal parameter identification in civil engineering.
Recently, we presented our genetic parameter identification in Brussels, Ludwig and Gerstmayr (2011).
We conclude that performing a reverse experiment is an indispensable tool for parameter identification in dipole tracer tests.
The proposed optimization algorithm can also be used for the static and/or dynamic parameter identification in robot calibration systems.
A general excitation condition is provided for parameter identification in so-called Liénard second order nonlinear systems.
The particle swarm optimization (PSO) algorithm has the random searching ability and has been widely applied to the parameter identification in the nonlinear dynamic hysteretic models.
A novel pattern recognition technique, support vector regression (SVR), has been introduced for linear structural parameter identification in a companion article.
The objectives were (i) to find an improved temporal measurement scheme for identification of these parameters using laboratory microlysimeter experiments and (ii) to evaluate the possibilities of parameter identification in the MACRO model.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com