Identification of semi-physical and black-box non-linear models: The case of MR-dampers for vehicles control

DOI10.1016/j.automatica.2004.08.012zbMath1060.93556OpenAlexW2041710184MaRDI QIDQ705448

Sergio M. Savaresi, Mauro Montiglio, Bittanti, Sergio

Publication date: 31 January 2005

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2004.08.012

zbMATH Keywords

Non-linear systemsGray-box modelMR-damperSemi-physical modelVehicles control

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Application models in control theory (93C95)

Related Items (10)

Application of joint coordinates and homogeneous transformations to modeling of vehicle dynamics ⋮ The hysteresis Bouc-Wen model, a survey ⋮ Variation of the hysteresis loop with the Bouc-Wen model parameters ⋮ Set membership inversion and robust control from data of nonlinear systems ⋮ Control of an automotive semi-active suspension ⋮ A limit cycle approach for the parametric identification of hysteretic systems ⋮ Smart‐Bogie: Semi‐Active Lateral Control of Railway Vehicles ⋮ Identification of the dynamic parametrical model with an iterative orthogonal forward regression algorithm ⋮ Semi active damping force estimation using \(LPV-H_\infty\) estimators with different sensing configurations ⋮ Discussion on: ``Comparison of different multivariable control design methods applied on half car test setup

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The effects of rapid sampling in system identification
• On covariance function tests used in system identification
• Approximate linearization via feedback -- an overview
• Non-linear system identification using closed-loop data with no external excitation: The case of a lean combustion chamber
• System identification using Laguerre models
• ESTIMATION OF AUTOREGRESSIVE MOVING-AVERAGE MODELS VIA HIGH-ORDER AUTOREGRESSIVE APPROXIMATIONS
• Quantification of model uncertainty from data
• On the design of approximate non-linear parametric controllers
• Hierarchically structured neural networks: A way to shape a `magma' of neurons

This page was built for publication: Identification of semi-physical and black-box non-linear models: The case of MR-dampers for vehicles control