Abstract
This paper deals with hardware implementation of the robust sensor fault detection and accommodation system of F8 aircraft control system. Both detection and accommodation of normal acceleration sensor is done using two different models of neural network. The simulation model of the novel method of fault accommodation is tested for timing constraints in the embedded system target of ARM processor. Longitudinal plant dynamics of F8 aircraft model and C-Star controller is used for validation of neural network based sensor fault detection and accommodation (NNSFA) system. The robust sensor fault accommodation system is implemented on ARM target of Atmel SAM3X8E ARM Cortex-M3 CPU. This board is inbuilt with ADC and DAC ports to interface pilot input command and the display of the cockpit.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
