Abstract
This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. Simulation results confirm the validity of the method and its capabilities with respect to some other methods.
| Lingua originale | English |
|---|---|
| Pagine | 3990-3995 |
| Numero di pagine | 6 |
| Stato di pubblicazione | Published - 2004 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modelling and Simulation
- Control and Optimization
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D'Ippolito, F., Alonge, F., Raimondi, F. M., & Tumminaro, S. (2004). Identification of Nonlinear Systems Described by Hammerstein Models. 3990-3995.