A review of damping models for structures with mechanical joints
AT Mathis, NN Balaji, RJ Kuether… - Applied …, 2020 - asmedigitalcollection.asme.org
In a standard design practice, it is often necessary to assemble engineered structures from
individually manufactured parts. Ideally, the assembled system should perform as if the …
individually manufactured parts. Ideally, the assembled system should perform as if the …
Nonlinear system identification: A user-oriented road map
J Schoukens, L Ljung - IEEE Control Systems Magazine, 2019 - ieeexplore.ieee.org
Nonlinear system identification is an extremely broad topic, since every system that is not
linear is nonlinear. That makes it impossible to give a full overview of all aspects of the fi eld …
linear is nonlinear. That makes it impossible to give a full overview of all aspects of the fi eld …
A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control
Hysteretic nonlinearity behavior ubiquitously occurs in mechanical systems, particularly in
high-precision instruments, which severely degrades system output performance …
high-precision instruments, which severely degrades system output performance …
An inverse identification strategy for the mechanical parameters of a phenomenological hysteretic constitutive model
An inverse strategy is developed for identifying the parameters of the hysteretic
phenomenological constitutive model presented in Vaiana et al.(2019) and belonging to a …
phenomenological constitutive model presented in Vaiana et al.(2019) and belonging to a …
Some practical regards on the application of the harmonic balance method for hysteresis models
Describing hysteretic systems with a closed-form solution is a challenging task due to some
pitfalls regarding the non-smooth and memory effect mechanisms that do not permit, for …
pitfalls regarding the non-smooth and memory effect mechanisms that do not permit, for …
Efficient hinging hyperplanes neural network and its application in nonlinear system identification
In this paper, the efficient hinging hyperplanes (EHH) neural network is proposed, which is
basically a single hidden layer neural network. Different from the dominant single hidden …
basically a single hidden layer neural network. Different from the dominant single hidden …
Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling
Nonlinear state-space modelling is a very powerful black-box modelling approach. However
powerful, the resulting models tend to be complex, described by a large number of …
powerful, the resulting models tend to be complex, described by a large number of …
Applying polynomial decoupling methods to the polynomial NARX model
K Karami, D Westwick, J Schoukens - Mechanical Systems and Signal …, 2021 - Elsevier
Abstract System identification uses measurements of a dynamic system's input and output to
reconstruct a mathematical model for that system. These can be mechanical, electrical …
reconstruct a mathematical model for that system. These can be mechanical, electrical …
On the initialization of nonlinear LFR model identification with the best linear approximation
M Schoukens, R Tóth - IFAC-PapersOnLine, 2020 - Elsevier
Balancing the model complexity and the representation capability towards the process to be
captured remains one of the main challenges in nonlinear system identification. One …
captured remains one of the main challenges in nonlinear system identification. One …
Decoupling multivariate polynomials for nonlinear state-space models
J Decuyper, P Dreesen, J Schoukens… - IEEE Control …, 2019 - ieeexplore.ieee.org
Multivariate polynomials are omnipresent in black-box modelling. They are praised for their
flexibility and ease of manipulation yet typically fall short in terms of insight and …
flexibility and ease of manipulation yet typically fall short in terms of insight and …