Abstract
This paper presents the sensor fault configuration through Neuro-Fuzzy. As we know that sensor faults have been observed in may domain. Various sensors faults are present such as bias, scaling, drift so to remove this kind of fault which is present we make the sensor to reconfigure to normal condition and this reconfiguration is done through Neuro-Fuzzy which uses the expert knowledge stored in them while training. This technique is implemented through ANFIS tool. Sugeno-Type fuzzy inference system is used, which is adaptive in nature and also Gaussian membership function is used. This technique uses the hybrid optimization which consists of combination of backpropagation and least square method algorithm. Simulation result is shown.
Sign-in/Register to access full text options 
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.
