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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 numerically robust mixed-integer quadratic programming solver for embedded hybrid model predictive control
The deployment of hybrid model predictive control (MPC) in practical applications requires
primarily an efficient and robust on-line Mixed-Integer Quadratic Programming (MIQP) solver …
primarily an efficient and robust on-line Mixed-Integer Quadratic Programming (MIQP) solver …
Identification of hybrid and linear parameter‐varying models via piecewise affine regression using mixed integer programming
This article presents a two‐stage algorithm for piecewise affine (PWA) regression. In the first
stage, a moving horizon strategy is employed to simultaneously estimate the model …
stage, a moving horizon strategy is employed to simultaneously estimate the model …
Rao-Blackwellized sampling for batch and recursive Bayesian inference of Piecewise Affine models
This paper addresses batch (offline) and recursive (online) Bayesian inference of Piecewise
Affine (PWA) regression models. By exploiting the particular structure of PWA models …
Affine (PWA) regression models. By exploiting the particular structure of PWA models …
Estimation of jump Box–Jenkins models
Abstract Jump Box–Jenkins (BJ) models are a collection of a finite set of linear dynamical
submodels in BJ form that switch over time, according to a Markov chain. This paper …
submodels in BJ form that switch over time, according to a Markov chain. This paper …
On hierarchical clustering-based identification of PWA model with model structure selection and application to automotive actuators for HiL simulation
Z Ren - Soft Computing, 2025 - Springer
The application of the electronic control unit (ECU) motivates dynamic models with high
precision to simulate mechatronic systems for various analysis and design tasks like …
precision to simulate mechatronic systems for various analysis and design tasks like …
Recursive bias-correction method for identification of piecewise affine output-error models
Learning PieceWise Affine Output-Error (PWA-OE) models from data requires to estimate a
finite set of affine output-error sub-models as well as a partition of the regressors space over …
finite set of affine output-error sub-models as well as a partition of the regressors space over …
Shrinkage strategies for structure selection and identification of piecewise affine models
We propose two optimization-based heuristics for structure selection and identification of
PieceWise Affine (PWA) models with exogenous inputs. The first method determines the …
PieceWise Affine (PWA) models with exogenous inputs. The first method determines the …
Energy disaggregation using piecewise affine regression and binary quadratic programming
In this paper we consider the problem of energy disaggregation, commonly referred in the
literature as “non-intrusive load monitoring”. The problem is to estimate the end-use power …
literature as “non-intrusive load monitoring”. The problem is to estimate the end-use power …
Exact and heuristic methods with warm-start for embedded mixed-integer quadratic programming based on accelerated dual gradient projection
Small-scale Mixed-Integer Quadratic Programming (MIQP) problems often arise in
embedded control and estimation applications. Driven by the need for algorithmic simplicity …
embedded control and estimation applications. Driven by the need for algorithmic simplicity …