IJE TRANSACTIONS C: Aspects Vol. 34, No. 03, (March 2021) 676-681
Please cite this article as: Z. Nejati, A. Faraji, Actuator Fault Detection and Isolation for Helicopter Unmanned Arial Vehicle in the Present of
Disturbance, International Journal of Engineering, Transactions C: Aspects Vol. 34, No. 03, (2021) 676-681
International Journal of Engineering
J o u r n a l H o m e p a g e : w w w . i j e . i r
Actuator Fault Detection and Isolation for Helicopter Unmanned Arial Vehicle in the
Present of Disturbance
Z. Nejati, A. Faraji*
Department of Electrical and Computer Engineering, University of Kashan, Kashan, Iran
P A P E R I N F O
Paper history:
Received 21 August 2020
Received in revised form 11 November 2020
Accepted 18 January 2021
Keywords:
Actuator Faults
Fault Detection
Fault Isolation
Helicopter Unmanned Arial Vehicle
Unknown Input Observer
A B S T R A C T
Helicopter unmanned aerial vehicle (HUAV) are an ideal platform for academic researchs. Abilities of
this vehicle to take off and landing vertically while performing hover flight and various flight maneuvers
have made them proper vehicles for a wide range of applications. This paper suggests a model-based
fault detection and isolation for HUAV in hover mode. Moreover in HUAV, roll, pitch and yaw actuator
faults are coupled and affect each other, hence, we need a method that decouples them and also separates
fault from disturbance. For this purpose, a robust unknown input observer (UIO) is designed to detect
bias fault and also catastrophic fault such as stuck in actuators of HUAV. The robust UIO isolates roll
and pitch actuator faults from yaw actuator fault. The novelty of this manuscript is the design of two
UIO observers to detect and decouple the faults of helicopter actuators, one for lateral and longitudinal
actuators and the other for pedal actuator. Also the proposed method is compared with extended Kalman
filter (EKF). Simulation results show effectiveness of the proposed method for detection and isolation
of actuator faults with less number of observers and it is able to decouple fault and disturbance effects.
doi: 10.5829/ije.2021.34.03c.12
Longitudinal and lateral stabilizer flapping angles
Main rotor blade restoring spring constant
Height of main rotor hub above center of mass
Roll, pitch, and yaw rates in body frame
Height of tail rotor axis above center of mass
main and tail rotor thrust
main and tail rotor counter-torque
To provide a safe flight with a helicopter unmanned aerial
vehicle (HUAV), it is necessary to detect its faults and
make emergency landings on time. The fault may occur
in sensors, controllers, or actuators. Loss of control is the
most important factor in air events [1]. This paper
addresses the additive faults such as bias and stuck in
case of an external disturbance.
In case of a bias fault, the control level always has a
constant difference between the actual and expected
deviation. In the stuck fault, the actuator is locked in a
*Corresponding Author Institutional Email: ar.faraji@kashanu.ac.ir
(A. Faraji)
place. In the last decade, some FDI methods have been
proposed to deal with actuator faults and enhance the
safety of various unmanned aerial vehicles UAVs.
A sliding mode observer (SMO) is designed for
detection, isolation and estimation of the actuator faults
for the quadrature nonlinear Lipschitz model for an
incipient fault that is more difficult to detect [1, 2].
Multiple model adaptive estimation (MMAE) method is
used to detect and isolate actuator or sensor faults [3, 4].
Two systematic algorithms, intelligent Output-Estimator
and Model-Free technique were presented that detect and
isolate actuator fault of quadrotor UAV [5]. Lee and Choi
