Models and methods for hybrid system identification: a systematic survey
Dynamical systems and processes that either exhibit non-smooth behaviours (eg through
logic control or natural phenomena) or work in different modes of operation are usually …
logic control or natural phenomena) or work in different modes of operation are usually …
A novel recursive approach for online identification of continuous‐time switched nonlinear systems
This article focuses on the identification of switched nonlinear systems, which are
characterized as a collection of nonlinear dynamical systems. Each nonlinear subsystem is …
characterized as a collection of nonlinear dynamical systems. Each nonlinear subsystem is …
Learning neural state-space models: Do we need a state estimator?
In recent years, several algorithms for system identification with neural state-space models
have been introduced. Most of the proposed approaches are aimed at reducing the …
have been introduced. Most of the proposed approaches are aimed at reducing the …
[HTML][HTML] Direct identification of continuous-time LPV state-space models via an integral architecture
In this paper, we present a block-structured architecture for direct identification of continuous-
time Linear Parameter-Varying (LPV) state-space models. The proposed architecture …
time Linear Parameter-Varying (LPV) state-space models. The proposed architecture …
From system models to class models: An in-context learning paradigm
Is it possible to understand the intricacies of a dynamical system not solely from its
input/output pattern, but also by observing the behavior of other systems within the same …
input/output pattern, but also by observing the behavior of other systems within the same …
Output-only identification of self-excited systems using discrete-time Lur'e models with application to a gas-turbine combustor
A self-excited system is a nonlinear system with the property that a constant input yields a
bounded, nonconvergent response. Nonlinear identification of self-excited systems is …
bounded, nonconvergent response. Nonlinear identification of self-excited systems is …
Energy optimization for intelligent hybrid electric vehicles based on hybrid system approach in a car‐following process
Y Zhou, R Wang, R Ding - Optimal Control Applications and …, 2022 - Wiley Online Library
Considering the hybrid dynamical characteristics of multimode hybrid electric vehicle during
a car‐following process, a novel energy management strategy based on hybrid system …
a car‐following process, a novel energy management strategy based on hybrid system …
Extension of a clustering identification approach to multivariable piecewise affine systems: Application to an industrial dryer
L Zeineb, A Kamel - … of Mechanical Engineers, Part I: Journal …, 2024 - journals.sagepub.com
The main objective of this paper is the extension of the clustering-based identification
approach to Multi-Input Multi-Output (MIMO) PieceWise Affine systems (PWA). This …
approach to Multi-Input Multi-Output (MIMO) PieceWise Affine systems (PWA). This …
In-context learning for model-free system identification
In traditional system identification, we estimate a model of an unknown dynamical system
based on given input/output sequences and available physical knowledge. Yet, is it also …
based on given input/output sequences and available physical knowledge. Yet, is it also …
[PDF][PDF] ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks.
Multistep prediction models are essential for the simulation and model-predictive control of
dynamical systems. Verifying the safety of such models is a multi-faceted problem requiring …
dynamical systems. Verifying the safety of such models is a multi-faceted problem requiring …