A continuous optimization framework for hybrid system identification

DOI10.1016/j.automatica.2011.01.020zbMath1219.93030OpenAlexW2083880268MaRDI QIDQ716147

Fabien Lauer, Gérard Bloch, René Victor Valqui Vidal

Publication date: 19 April 2011

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2011.01.020

zbMATH Keywords

identificationhybrid systemrobustness to outlierslarge data set

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) System identification (93B30) Discrete-time control/observation systems (93C55) Large-scale systems (93A15)

Related Items

Global optimization for low-dimensional switching linear regression and bounded-error estimation, On the complexity of switching linear regression, Model structure selection for switched NARX system identification: a randomized approach, Data-driven switching modeling for MPC using regression trees and random forests, Minimality and identifiability of discrete‐time switched autoregressive exogenous systems, Identification of switched autoregressive exogenous systems from large noisy datasets, Stubborn state observers for linear time-invariant systems, Data-driven designs of observers and controllers via solving model matching problems, On the complexity of piecewise affine system identification, Synthesis of hybrid automata with affine dynamics from time-series data, Recursive estimation in piecewise affine systems using parameter identifiers and concurrent learning, A randomized two-stage iterative method for switched nonlinear systems identification, An Iterative Algebraic Geometric Approach for Identification of Switched ARX Models with Noise, A statistical learning perspective on switched linear system identification, Set membership identification of switched linear systems with known number of subsystems, Moving-horizon estimation with guaranteed robustness for discrete-time linear systems and measurements subject to outliers

Uses Software

• MCS

Cites Work

• Recursive identification of switched ARX systems
• Global optimization by multilevel coordinate search
• Identification of piecewise affine systems via mixed-integer programming.
• A clustering technique for the identification of piecewise affine systems
• Identification of piecewise affine systems based on statistical clustering technique
• Switched and PieceWise Nonlinear Hybrid System Identification
• A Bayesian approach to identification of hybrid systems
• A bounded-error approach to piecewise affine system identification
• Hybrid Systems: Computation and Control