The paper is concerned with an innovative air-data sensor calibration procedure, carried out through neuro-fuzzy techniques based on adaptive neuro-fuzzy inference system (ANFIS) and co-active neuro-fuzzy inference system (CANFIS) models. In particular, attention is focused on a beta sideslip angle virtual sensor, and data used for the calibration are obtained through a series of simulations performed by means of the nonlinear dynamic model in 6 degrees of freedom of a high-performance combat aircraft. Several ANFIS and CANFIS architectures have been developed, tested, and compared with each other. Results of numerical simulations show the remarkable effectiveness of neuro-fuzzy techniques in the sensor calibration.
Neuro-Fuzzy Techniques for the Air-Data Sensor Calibration / M. LANDO; BATTIPEDE M.; P. GILI. - In: JOURNAL OF AIRCRAFT. - ISSN 0021-8669. - STAMPA. - 44:2(2007), pp. 945-953. [10.2514/1.26030]
|Titolo:||Neuro-Fuzzy Techniques for the Air-Data Sensor Calibration|
|Data di pubblicazione:||2007|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.2514/1.26030|
|Appare nelle tipologie:||1.1 Articolo in rivista|