A nonlinear state-space approach to hysteresis identification
| Autor: | Gaëtan Kerschen, Joannes Schoukens, Jean-Philippe Noël, Alireza Fakhrizadeh Esfahani |
|---|---|
| Přispěvatelé: | Electricity, Faculty of Engineering, Thermodynamics and Fluid Mechanics Group |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Signal processing
0209 industrial biotechnology Engineering State variable dynamic nonlinearity Aerospace Engineering 02 engineering and technology Systems and Control (eess.SY) state-space models 01 natural sciences 020901 industrial engineering & automation Control theory 0103 physical sciences FOS: Electrical engineering electronic engineering information engineering State space Degree of a polynomial Representation (mathematics) 010301 acoustics Civil and Structural Engineering Nonlinear system identification business.industry Mechanical Engineering black-box method Computer Science Applications Nonlinear system Hysteresis hysteresis Control and Systems Engineering Computer Science - Systems and Control Bouc–Wen model of hysteresis business |
| Popis: | Most studies tackling hysteresis identification in the technical literature follow white-box approaches, i.e. they rely on the assumption that measured data obey a specific hysteretic model. Such an assumption may be a hard requirement to handle in real applications, since hysteresis is a highly individualistic nonlinear behaviour. The present paper adopts a black-box approach based on nonlinear state-space models to identify hysteresis dynamics. This approach is shown to provide a general framework to hysteresis identification, featuring flexibility and parsimony of representation. Nonlinear model terms are constructed as a multivariate polynomial in the state variables, and parameter estimation is performed by minimising weighted least-squares cost functions. Technical issues, including the selection of the model order and the polynomial degree, are discussed, and model validation is achieved in both broadband and sine conditions. The study is carried out numerically by exploiting synthetic data generated via the Bouc–Wen equations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|