UAV actuator fault detection through artificial intelligent technique

Zulhilmy Sahwee, Aina Suriani Mahmood, Nazaruddin Abd Rahman, Khairul Salleh Mohamed Sahari

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)141-154
Number of pages14
JournalJournal of Mechanical Engineering
Volume5
Issue numberSpecialissue6
Publication statusPublished - 01 Jan 2018

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Fuzzy inference
Unmanned aerial vehicles (UAV)
Fault detection
Actuators
Membership functions
Failure analysis
Aircraft
Uncertainty

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Cite this

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UAV actuator fault detection through artificial intelligent technique. / Sahwee, Zulhilmy; Mahmood, Aina Suriani; Abd Rahman, Nazaruddin; Mohamed Sahari, Khairul Salleh.

In: Journal of Mechanical Engineering, Vol. 5, No. Specialissue6, 01.01.2018, p. 141-154.

Research output: Contribution to journalArticle

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