Aerospace and Electronic Systems Magazine July 2018 - 21

Shraim, Awada, and Youness
of the Monte Carlo simulations, and the approach does not ensure
a collision-free trajectory [130].
Another interesting approach based on visual sensor and geometrical calculation in 3D is presented in [131]. Here, obstacles
were detected by using descriptor vectors of two images (detected
by two cameras) and the matching between them. This strategy is
based on a computer vision technique named SURF.
Other types include the Force field approach presented in
[132]; the Bearing angle-based approach presented in [133]-[135];
the Optimized trajectory approach presented in [36], [136]; and the
Geometric approach presented in [137], [138].

FAULT DIAGNOSIS AND FAULT TOLERANT CONTROL
Fault diagnosis is an important field in modern control theory
[139]-[143]. Several researchers have illustrated and focused on
the important problem of detecting and isolating sensor faults on
quadrotors [144]-[146]. The nonlinearity of such systems makes
it difficult to exploit significant developments which in the area
of fault detection in linear systems [147]. There are several studies treating the fault diagnosis problem as it applies to quadrotors
[148]-[152].
Most quadrotors used in research are equipped with inertial measurement units (IMU), including a three-axis gyro, an
accelerometer, and a magnetometer. Signals issued from these
sensors play an essential role in most quadrotor controllers.
However, IMUs are subjected to exogenous signals and prone to
faults. Specifically, accelerometer and gyroscope measurements
are susceptible to bias and excessive noise due to variations of
temperature, vibration, etc. The detection and estimation of accelerometer and gyroscope faults play a crucial role in the safe
operations of quadrotors [153].
Several studies treat the problem of IMU sensor fault diagnosis
based on a linearized model of the system [151], [154-156]. Some
studies generate residuals based on the Luenberger or Kalman filter-based observers for fault diagnosis [151], [155], [157]. Due to
the highly nonlinear dynamics of the quadrotor, an important effort
has been oriented towards the nonlinear model of the quadrotors
[158] and nonlinear adaptive estimation techniques [159], [160].
One solution for quadrotor fault diagnosis has been developed based on the differential algebraic approach [161]. Using
this approach, it is possible to generate residuals for fault diagnosis with the construction of a bank of observers [162], as well as
develop a control strategy based on the state estimation [163]. In
[164], the authors present a reduced order sliding mode observer
to reconstruct fault when one output is available in a three-tank
system. A reduced order observer and an algebraic observer are
presented in [165]. [166] presents a polynomial observer; a reduced order observer and a sliding mode observer are used to
estimate the system states and faults in the case of multiple available outputs. Observability and Diagnosability Condition are presented in [167].
In [168], the authors mention that the quadrotor is controlled
over a real time communication network with time varying delays. Therefore, it can be considered a networked control system
(NCS). This work proposes a solution for the attitude sensor fault
JULY 2018

diagnosis in a quadrotor helicopter. Considerable attention in the
automatic control community has been given to the NCS, such as
in [169]-[174]. The main focus of these activities is oriented towards the system performance analysis with respect to technical
properties of the network and its controller design schemes [175],
[176]. It is worth noting that the implementation of the communication network in the closed loop system makes the analysis
and the synthesis of the NCSs a highly complex task [177]. When
dealing with the NCS, the network induced effects that may arise
include time delays [173], [177]-[185] and quantization problems [169], [186], [187]. Fault detection (FD) of the NCS is a new
research topic [188]. Work presented in [189]-[193] focuses on
networked-induced delays. The authors of [194] present a method
for fault detection in NCS systems under stochastic and probably
long duration delay. The model given in [195] and [196] is adopted
for the design.
Others [197], [198] have treated the problem of analysis and
design of FD systems in the case of missing measurements. The
possibility of detecting and isolating fault (fault detectability and
isolability) in NCS systems has been analyzed in [193], [199],
[200]. The fault tolerant structure has been studied in [201]-[203].
In [204], the authors mention that the majority of fault detection approaches of NCSs existing in the literature are model based.
However, artificial intelligence methods are considered less suitable for real time implementation [205]. Development on FDD
techniques can also be found in [206], [207]. For information on
FDD techniques applied to UAV and satellite systems, see [207]-
[211].
An FTC system is a control system with the ability to automatically tolerate a fault occurring on one component during system
operation [16], [17], [34], [212]. In order to enhance the reliability,
survivability, and autonomy of UAVs, advanced intelligent control and health management technologies are required, which will
enable UAVs to have the capabilities of state awareness and selfadaptation [156], [213].
A few works address the control of quadrotors for normal and
faulty conditions using a multiobserver switching strategy [18].
Reference [19] presents an observer for systems with partial sensor failures, while [20] examines the use of a gain scheduling based
PID controller. In the latter, partial faults in an actuator can be detected; the controller then reconfigures in such a way as to maintain stability and performance of the faulty system. This work also
proposes a method based on the reference governor.

DISCUSSION
In general, this section can be divided into three main parts: discussion of proposed methods and strategies, discussion of mission
scenarios and proposed strategies, and case study and comparative
study.

DISCUSSION OF PROPOSED METHODS AND STRATEGIES
1. Concerning the model, a full nonlinear model has been obtained by the application of classical mechanics methods such
as Euler-Newtonian and Lagrange formalism. It is worth not-

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