| Autor: |
Edward Winward, Zhijia Yang, Byron Mason, Mark Cary |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 10, Pp 8653-8663 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2021.3138166 |
| Popis: |
The appropriate choice of excitation signal in system identification is an important part of the process that determines the success of many downstream activities. For a complex system with high dimensional nonlinear behaviour, excitation signal design is non-trivial. This paper presents a novel methodology for excitation signal design to create high accuracy multivariable nonlinear dynamic neuro-fuzzy models. Two different approaches to experimental design are investigated. In the first, a prescribed transient manoeuvre is used. In the second, informative potential is used to deconstruct the transient into a sequence of inputs designed to cover the same input space and reduce model development time. Star discrepancy is used to evaluate the resulting designs and is shown to provide a good proxy for excitation design quality. Results are presented showing the prediction accuracy of the model in terms of an application example, achieving a minimum |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
