UAV actuator fault detection through artificial intelligent technique / Zulhilmy Sahwee ... [et al.]

• Main Authors: Sahwee, Zulhilmy (Author), Mahmood, Aina Suriani (Author), Abd. Rahman, Nazaruddin (Author), Mohamed Sahari, Khairul Salleh (Author)
• Format: Book
• Published: Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), 2018.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/40960/1/40960.pdf
• Keywords: Engineering mathematics. Engineering analysis; TJ Mechanical engineering and machinery

The design of Fault Detection and Diagnosis (FDD) is a tedious and challenging task. It is due to the changes and uncertainties associated with the aircraft dynamics following an occurrence of a fault. It was believed that until recently, the control reallocation following a system fault was too complex and computationally intensive for real world flight control cases. However, the recent, a dramatic improvement in computer speed and the development of more efficient algorithms have changed the situation considerably. This paper presents an artificial intelligent, in specific using Fuzzy Inference System method to detect an actuator fault. Three ground simulations were performed to validate the performances of the fault detection technique proposed. The residuals were evaluated by using three membership functions of the Fuzzy Inference System. The results show that the proposed technique was able to detect the actuator fault.