Name
Abstract | ||
|---|---|---|
Results on experiment design for the identification of nonlinear systems are extremely scarce. This paper examines the identification and optimal input design for a very simple nonlinear system: a Wiener system composed of a Finite Impulse Response (FIR) system followed by a power nonlinearity: (.)n. We first show that an expanding power (n >; 1) increases the information about the estimated parameters, while a compressing power (0 <; n <; 1) decreases the information. We then formulate a simple optimal input design problem for the considered class of Wiener systems and show that solutions can be computed by restricting the class of considered input signals. We provide a solution which offers some intuitive insights for the case of a FIR(2) system with a square nonlinearity and where the inputs are restricted to be Gaussian. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CDC.2012.6425915 | Decision and Control |
Keywords | Field | DocType |
FIR filters,nonlinear systems,parameter estimation,stochastic processes,FIR(2) system,Wiener system identification,finite impulse response system,nonlinear system identification,optimal input design problem,parameter estimation,power nonlinearity,square nonlinearity | Mathematical optimization,Nonlinear system,Control theory,Computer science,Stochastic process,Nonlinear system identification,Gaussian,Input design,Estimation theory,Finite impulse response,Design of experiments | Conference |
ISSN | ISBN | Citations |
0743-1546 E-ISBN : 978-1-4673-2064-1 | 978-1-4673-2064-1 | 3 |
PageRank | References | Authors |
0.44 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michel Gevers | 1 | 506 | 106.82 |
| Matthias Caenepeel | 2 | 3 | 0.44 |
| Johan Schoukens | 3 | 376 | 58.12 |