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 …
Modeling and identification of nonlinear systems: A review of the multimodel approach—Part 1
The efficacy of the multimodel framework (MMF) in modeling and identification of complex,
nonlinear, and uncertain systems has been widely recognized in the literature owing to its …
nonlinear, and uncertain systems has been widely recognized in the literature owing to its …
Modeling and identification of nonlinear systems: A review of the multimodel approach—Part 2
The efficacy of the multimodel framework (MMF) in modeling and identification of complex,
nonlinear, and uncertain systems has been widely recognized in the literature owing to its …
nonlinear, and uncertain systems has been widely recognized in the literature owing to its …
Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system
A new approach for structural health monitoring using guided waves in plate-like structures
has been developed. In contrast to previous approaches, which mainly focused on isotropic …
has been developed. In contrast to previous approaches, which mainly focused on isotropic …
Real time estimation of impaired aircraft flight envelope using feedforward neural networks
Extensive research in recent years has focused on develo** flight envelope estimation
methods to improve current loss of control prevention and recovery systems. Such methods …
methods to improve current loss of control prevention and recovery systems. Such methods …
Nonlinear system identification by Gustafson–Kessel fuzzy clustering and supervised local model network learning for the drug absorption spectra process
This paper deals with the problem of fuzzy nonlinear model identification in the framework of
a local model network (LMN). A new iterative identification approach is proposed, where …
a local model network (LMN). A new iterative identification approach is proposed, where …
Polytopic black-box modeling of dc-dc converters
The objective of this work is to develop modular black-box converter models for system-level
design and analysis that are valid in a wide variety of operating conditions. The approach …
design and analysis that are valid in a wide variety of operating conditions. The approach …
Supervised hierarchical clustering in fuzzy model identification
This paper presents a new, supervised, hierarchical clustering algorithm (SUHICLUST) for
fuzzy model identification. The presented algorithm solves the problem of global model …
fuzzy model identification. The presented algorithm solves the problem of global model …
Iterative excitation signal design for nonlinear dynamic black-box models
TO Heinz, O Nelles - Procedia computer science, 2017 - Elsevier
A new method to generate excitation signals for the identification of nonlinear dynamic
processes is introduced. The objective of the optimization is a uniform data point distribution …
processes is introduced. The objective of the optimization is a uniform data point distribution …
Nonlinear power system load identification using local model networks
This paper proposes a local model network (LMN) for measurement-based modeling of the
nonlinear aggregate power system loads. The proposed LMN approach requires no pre …
nonlinear aggregate power system loads. The proposed LMN approach requires no pre …