Dynamic Model of UAV

This study material provides an in-depth understanding of the dynamic modeling of Unmanned Aerial Vehicles (UAVs). It covers the equations and principles used in dynamic modeling and control of UAVs. The material also discusses the applications of dynamic UAVs, including humanitarian relief. The content includes a literature review, sample models, and references to relevant research papers.

Dynamic Model of UAV
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Abstract
1. Introduction
2. Literature Review
The use of Unmanned Aerial Vehicles began
in the early 90’s due to military development.
Originally, unmanned vehicles were designed
for use in places where humans could not reach.
Compared to manned crafts, UAVs were
initially used for operations that were too '
tedious, nasty or harmful for human beings,
whereas they emerged primarily in military
purposes, their use rapidly expanded to industry,
science, recreational, horticultural and solution
applications, such as police, peacemaking and
police investigations, deliveries of products,
aerial photography, trafficking and drones.
Civilian UAVs currently immensely add up
military UAVs, with estimates of over 1 million
sold-out by 2016.
Motivated by a desire to utilize UAVs in an
urban setting, involvement in Vertical Take-Off
and Landing (VTOL) mini Air Vehicles (mAVs)
has doubled dramatically in recent years.
Globally, many principles were implemented.
The Bidule mAV was built up at Sydney Uni to
examine small flight device design problems.
The beta version, the Bidule CSyRex, is a joint
venture in both Sydney College and Compiègne
School of Technology to create a Bidule VTOL
version (Guerrero & Lozano, 2012).
Dynamic modeling is an essential step in a
dynamic system's production and control.
Depending on different conditions, the approach
allows the engineer to evaluate the model, its
potential and its behavior. In addition, dynamic
models are commonly used in the design of
controls (Noth, Bouabdallah & Siegwart, 2019).
A sample model of UAV system include
that which was modelled and presented to
International Conference on Innovative
Computing Technology in 2017. The paper is
Focused on quadrotor modelling and regulation;
first moments and torque modeling; second rotor
modeling; the result with full UAV dynamics.
The conceptual model is presented for a general
study with disturbance and we take into
consideration all control parameters. The PID
control system is identified without disturbance
in a dynamic formula for a sequential system,
where we use it to control a group of quadrotors
to avoid collisions, and a group of quadrotors
with rigid and responsive URLs to supply
payloads in a free zone (Bravo & Leiras, 2015).
Application of Dynamic UAV’s have
increased, the recent development being
Humanitarian relief. Since 2001, unmanned
aerial vehicles (UAVs) or drones have been used
in humanitarian response following the 9/11
terror attack. UAV aerial imaging offers key
information for professional developers and
choice - producers to analyze and act effectively.
According to Meier (2014), in reaction to a
disaster, quite small and compact UAVs are
already used to take high-pixel density visuals,
the application of Dynamic UAV models will
son expand to micro transportation fields.
Google has manufactured and evaluated
autonomous aircrafts and believes they can be
used to transport goods (Kamel et al,2017).
Turboprop UAVs have much more strength
and endurance than Fixed wing UAVs, but for
landing and taking they need runways as well as
other liftoff frameworks. In this case, rotary
wing UAVs are more flexible and adaptable as
they don't need runways to land and take off.
Hey can navigate easily via tight areas and
indoors. Therefore, Rotary wing UAVs are
generally preferred due to extreme o their
flexibility (Tahir et al., 2016).
The main equations used in modelling
dynamic systems have been shown below
Dynamic systems are described by equations
of motions given below.

These equations will be explained below.
dx/dt = f(x,p),
The integral equations defines the Semi-Explicit
Form equation relating to motion
f(dx/dt,x,p)=0, Open Equation Form
Equations describing motion in relation to force
F = m a
The above equations represent the relation of
mass and acceleration with respect to force
acting on an object. The force applied is directly
proportional to mass and acceleration
dy/dt = v
the differentials of distance with relation to time
gives velocity of an object.
dv/dt = a (Al-Sharman et al., 2019)
The equation above describes the relation of
velocity with acceleration. The differential of
velocity with respect to time gives acceleration
from the equations above, we can derive all the
dynamic modelling equations.
state space equations (Al-Sharman et al., 2019)
The state space equations describe the behavior
of a dynamic system as a set of first order
ordinary differential equations (ODE).
The x,y and z describes the state vectors of the
motion.
The whole equation describes the state matrix of
the system model
rotation matrix equation for describing rotary
motions (Al-Sharman et al., 2019)
The equation above describes the rotation on all
axis of the system.
Roation on each axis that is, X,Y and Z are
described individually as shown below,

The matrixes above describe the individual
rotation on different axis. Combining all the
three rotation matrixes results to a general
rotation matrix as discuss above.
Bibliography
Abu Hassan, S. (2014). Effective Range of
Unmanned Aerial Vehicle (UAV) in the
Malaysian Army Tactical
Operations. Applied Mechanics And
Materials, 629, 399-403. doi:
10.4028/www.scientific.net/amm.629.399
Al-Sharman, M., Zweiri, Y., Jaradat, M., Al-
Husari, R., Gan, D., & Seneviratne, L.
(2019). Deep-Learning-Based Neural
Network Training for State Estimation
Enhancement: Application to Attitude
Estimation. IEEE Transactions On
Instrumentation And Measurement, 1-11.
doi: 10.1109/tim.2019.2895495
Bhattacharjee, D. (2015). Unmanned Aerial
Vehicles and Counter Terrorism
Operations. SSRN Electronic Journal. doi:
10.2139/ssrn.2608969
Bravo, R., & Leiras, A. (2015). Literature
review of the applications of UAVs in
humanitarian relief (1st ed.). Fortaleza, CE,
Brasil.
Coe, J., Dunbar, C., Epps, K., Hagensee, J., &
Moore, A. (2019). A Low-altitude
Unmanned Aerial Vehicle (UAV) Created
Using 3D-printed Bioplastic. Journal Of
Unmanned Vehicle Systems. doi:
10.1139/juvs-2017-0023
Erbe, C., Parsons, M., Duncan, A., Osterrieder,
S., & Allen, K. (2017). Aerial and
underwater sound of unmanned aerial
vehicles (UAV, drones). Journal Of
Unmanned Vehicle Systems. doi:
10.1139/juvs-2016-0018
Erbe, C., Parsons, M., Duncan, A., Osterrieder,
S., & Allen, K. (2017). Aerial and
underwater sound of unmanned aerial
vehicles (UAV, drones). Journal Of
Unmanned Vehicle Systems. doi:
10.1139/juvs-2016-0018
Farhadi, R. (2017). ROBUST PID CONTROL
TUNING FOR THE UNCERTAIN
NONLINEAR DYNAMIC MODEL OF
THE UNMANNED AERIAL
VEHICLE. Electronics And Control
Systems, 3(53). doi: 10.18372/1990-
5548.53.12143
Guerrero, J., & Lozano, R. (2012). Flight
Formation Control (pp. 99-134). New York,
NY: John Wiley & Sons.
Kamel, B., Yasmina, B., Laredj, B.,
Benaoumeur, I., & Zoubir, A. F. (2017,
August). Dynamic modeling, simulation and
PID controller of unmanned aerial vehicle
UAV. In 2017 Seventh International
Conference on Innovative Computing
Technology (INTECH) (pp. 64-69). IEEE.
Li, R., Shi, Y., & Xu, H. (2013). Integrated PID
controller design for an unmanned aerial
vehicle with static stability. ANZIAM
Journal, 54, 200. doi:
10.21914/anziamj.v54i0.5169

Li, R., Shi, Y., & Xu, H. (2013). Integrated PID
controller design for an unmanned aerial
vehicle with static stability. ANZIAM
Journal, 54, 200. doi:
10.21914/anziamj.v54i0.5169
Noth, A., Bouabdallah, & Siegwart, R. (2019).
Autonomous Systems Laboratory. Dynamic
Modeling Of Fixed-Wing Uavs, 2, 3.
Shamma, S., Alkhoori, F., Zweiri, Y., &
Sahinkaya. (2019). Implementation of a
Novel Optimal PID Methods in UAV
Applications [Ebook] (1st ed.). 2018 3rd
International Conference on Advanced
Robotics and Mechatronics (ICARM).
SZABOLCSI, R. (2018). OPTIMAL PID
CONTROLLER BASED AUTOPILOT
DESIGN AND SYSTEM MODELLING
FOR SMALL UNMANNED AERIAL
VEHICLE. Review Of The Air Force
Academy, 16(3), 43-58. doi: 10.19062/1842-
9238.2018.16.3.6
Szczepaniak, P., & Jóźko, M. (2017). Research
of Pneumatic Distributors for Launcher of
Unmanned Aerial Vehicle (UAV). Journal
Of Konbin, 43(1), 249-276. doi:
10.1515/jok-2017-0049
Tahir, Z., Jamil, M., Ali Liaqat, S., Mubarak, L.,
Tahir, W., & Omer Gilani, S. (2016). Design
and Development of Optimal Control
System for Quad Copter UAV. Indian
Journal Of Science And Technology, 9(25).
doi: 10.17485/ijst/2016/v9i25/96611
TAO, Y. (2009). Design and Realization of
Piecewise PID Controller with Deadzone for
Micro UAV. Acta Automatica Sinica, 34(6),
716-720. doi: 10.3724/sp.j.1004.2008.00716