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, Manuela; Gili, Piero. - In: JOURNAL OF AIRCRAFT. - ISSN 0021-8669. - STAMPA. - 44:2(2007), pp. 945-953. [10.2514/1.26030]
Neuro-Fuzzy Techniques for the Air-Data Sensor Calibration
BATTIPEDE, Manuela;GILI, Piero
2007
Abstract
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.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/1605205
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo