C O V E N T R Y
U N I V E R S I T Y
Faculty of Engineering and Computing
Department of Aerospace Engineering
BEng Aerospace Technology
388SYS Individual Project
UAVS Project 2009
Author: UBAIER AHMAD BHAT
Supervisor: DR. S M HARGRAVE
Submitted in partial fulfilment of the requirements for the Degree of Bachelor of
Aerospace Technology
2008 - 2009
“I have not failed. I've just found ten
thousand ways that won't work.”
--Thomas Alva Edison
DECLARATION
The work described in this report is the result of my own investigations. All sections
of the text and results that have been obtained from other work are fully referenced.
The dissertation and the original work related to it have not been submitted to any
institute for an academic award. I understand that cheating and plagiarism constitute
a breach of University Regulations and will be dealt with accordingly.
Signed: Date:
i
ABSTRACT
Bhat, U. 2009. UAV Project 2009, BEng Aerospace Technology
Dissertation. Faculty of Engineering and Computing, Coventry
University.
Unmanned Arial Vehicles have seen an unprecedented growth in recent years
in both military as well as civilian application domain. This has increased the
interest and research in unmanned technology at academic level. Coventry
University as also invested in technology related to development of UAVs like
an autopilot and flight simulators. This report details the work done on
implementation of an autopilot system on UAV and simulation of the aircraft.
The approach used for this project was to get familiar with the autopilot
system (Micropilot MP2028g) and install it onto an aircraft. The project also
involved an attempt to simulate and analyse of the pitch dynamics of the
aircraft model acquired.
The autopilot was implemented on a test aircraft and was tested on ground
but a flight test did not take place. Different packages for simulations and
problems related to them were also investigated.
Keywords: unmanned aerial vehicle, UAV, autopilots, flight simulation,
modelling.
ii
CONTENTS
Declaration i
Abstract ii
Table of Contents iii
Acknowledgements and Dedication v
1. INTRODUCTION 1
1.1 Aims and Objectives of the Project 1
1.2 Outline of the Report 1
1.3 Modifications to project aim. 2
2. LITERATURE REVIEW 3
2.1 Unmanned Arial Vehicles 3
2.1.1 Introduction 3
2.1.2 Types of UAVs 3
2.1.3 Components of a UAV System 5
2.1.4 Applications 6
2.2 Stability and Automation of UAVs 8
2.3 Dynamics of Flight 10
2.3.1 Introduction 10
2.3.2 Six Degrees of Freedom (6DOF) 10
2.3.3 Pitch dynamics and Longitudinal stability 10
2.4 Modelling and Simulations 12
2.4.1 Introduction 12
2.4.2 Modelling and Simulation Techniques 12
2.4.3 Applications 12
2.4.4 Problems 13
2.5 System Identification 14
3. UAV PLATFORM 15
3.1 INTRODUCTION 15
3.2 TEST PLANE 15
3.3 2009 UAV PLATFORM 18
4. THE AUTOPILOT 20
4.1 Introduction 20
4.2 Components 20
4.3 Installation 22
iii
4.4 Working and Configuration 23
4.5 Problems 23
5. FLIGHT SIMULATOR 25
5.1 Introduction 25
5.2 Merlin Flight Simulator 25
5.3 Flight Simulation Modals 28
5.4 Flight Tests 28
6. System Identification using AeroSim 33
7. Conclusion 39
8. Further Work and Recommendations 40
9. References 41
10. Bibliography 42
11. Appendixes
A Initial Documentation and Interim Report I
B Test Results IX
iv
ACKNOWLEDGEMENTS AND DEDICATIONS
I would like to thank Dr. Stephen Hargrave for supervising the project and helping
me throughout the course. I would also like to thank Mr. Basini, Mr. Fisher, Dr.
Lambert and Mr. Thorley for their help for the project and the course.
I would also like to thank fellow students Mohammad Bahrami, Arnaud Dupin,
Thomas Gobeaut, Douglas Mackenzie and Kelvin Nelson.
I would like to thank Allah for giving be strength and patience throughout the project
and the course. I would also like to thank my family for their financial and emotional
support.
I would also like to dedicate this project to those innocent children who have been
killed in UAV strikes worldwide and pray that the unmanned technology is not used
for any inhumane activities.
v
CHAPTER 1: INTRODUCTION
CHAPTER 1: INTRODUCTION
1.1 Aims and Objectives of the Report
The report presents the details of the work done on implementation of MicroPilot
MP2028g autopilot on the UAV platforms developed in the university. The report also
presents the results of research into the modelling and simulation of the UAV. The
main objectives set for the project were as follows:
1. Familiarisation and implementation of the MicroPilot 2028
2. Familiarisation with Merlin Flight Simulator and modelling and simulation of
the UAV.
3. System identification and generation of linearised model of the pitch dynamics
of the aircraft.
1.2 Outline of the Report
Chapter 2: Literature Review:
This chapter background information about UAVs and their applications, Automation
of aircrafts, modelling and simulation of systems.
Chapter 3: UAV platform
This chapter gives details about the UAV platforms used for the project.
Chapter 4: Autopilot
In this chapter details about the MicroPilot MP2028g along with some information
related to installations and setup.
Chapter 5: Flight Simulation
This chapter contains detailed information about Merlin Flight simulators and gives
some details modelling and simulation of the aircraft.
Chapter 6: System Identification
This chapter contains some details about AeroSim Blockset.
Chapter 7: Conclusion
Chapter 8: Further Work and Recommendations
References
Bibliography
Appendix A:
This Appendix contains the initial documentation and the interim report of the project.
Appendix B
This Appendix contains the flight test and simulation results.
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CHAPTER 1: INTRODUCTION
1.3 Modifications to the project aims
Initially it was planned to use Merlin Flight Simulator for simulation and modelling
purpose but due to some reason, which are discussed later in the report, this was
changed to AeroSim Blockset. This had a major effect on the aims that the project
had initially set to in regards to simulations.
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CHAPTER 2: LITERATURE REVIEW
CHAPTER 2: LITERATURE REVIEW
2.1 Unmanned Arial Vehicles
2.1.1 Introduction
An Unmanned Arial Vehicles (or UAV), also known as a drone, is an aircraft without
a human operator on board (MSN Encarta c. 2008). UAVs are different that guided
missile or cruise missiles in that the air vehicle is designed to come back and be re-
used. These are also different from normal remote controlled aircrafts in that they
have a high technology control systems on board which means can operate out of
line of sight and at altitudes where person on the ground cannot readily see them.
These air vehicles still need a pilot or an operator who rather than being seated in
the aircraft itself is located in a control centre normally referred to as a Ground
Control Station. (UAVSA c. 2008).
2.1.2 Types of UAVs
2.1.2.1 Classification by Aircraft Configuration
In general an aircraft is any flying machine/vehicle in all possible configuration be it
fixed-wing, rotary-wing, a balloon or an airship and potentially any aircraft can be
converted into an UAV with the right technology and control systems installed on
board (Beggs 2009). Therefore one of the ways classifying different types of UAVs is
by type of aircraft configuration.
a) Fixed wing UAV
These are the most common types
of UAVs and are currently being
used for wide range of
applications. These can be of
different sizes like the big Northrop
Grumman Global Hawk with a
wing span of 39.9m (Northrop
Grumman 2007a) to the small
backpack Casper form Becker
Avionics with a wing span of just
2.5 m (Becker Avionics 2006).
Some examples of different size
and range fixed wing UAVs can be
seen in figure 2.1a
One of the reasons for the
success of fixed wing UAVs is that
these are quite stable and require Figure 2.1a Examples of some fixed wing UAVs (BBC
simpler systems to control News 2009)
compared to other configurations.
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CHAPTER 2: LITERATURE REVIEW
b) Rotary-wing UAVs
There has been a lot of development in rotary-wing UAVs in recent years. The
manoeuvrability and the ability to maintain the aircraft in hovering of a Rotary wing
UAVs or a helicopter UAV present several advantages for UAV applications.
However, rotary-wing aircrafts are very unstable and therefore more difficult to
control and require the application of reliable control laws. (Remub et al. 2007:111)
Northrop Grumman MQ-8B Fire Scout is an A-160 Hummingbird by Boeing/Frontier
advanced rotary-wing UAV (US OSD 2005)
(Northrop Grumman 2007)
Figure 2.1b Examples of Rotary-wing UAVs.
c) Airship UAVs
A number of unmanned airship projects, both free-flying and tethered (aerostats),
have been initiated to provide synergistic capabilities to those provided by unmanned
aircraft, most notably extended persistence. There appears to be potential for
synergy between airships and UAS that enhance capability or reduce cost in several
mission applications including force protection, signals intelligence collection,
communications relay and navigation enhancement. An airship UAV’s most
significant challenge appears to be limited mobility. (US OSD 2005:32)
Example of some Airship UAVs can be seen in Figure 2.1c
Advanced Airship Flying Laboratory by American Tethered Aerostat Radar System (TARS) by ILC
Blimp Corporation Dover
Figure 2.1c Types of UAVs (US OSD 2005)
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CHAPTER 2: LITERATURE REVIEW
2.1.2.2 Classification by Autonomy
Based on the autonomy of the flight control system the UAVs can be categorised into
three main levels:
Level 1: no autonomy on-board the aircraft. This will be more like a remote controlled
aircraft (similar to a hobby plane). However different systems on-board the aircraft
like sensors, cameras, GPS receivers and transmitters can be used to assist the on
ground operator to fly the air craft out of sight.
Level 2: semi-autonomous aircraft with autopilot on-board to keep the aircraft stable.
Difficult tasks like landing and takeoff will still be carried out remotely by a human
pilot
Level 3: fully-autonomous aircraft with onboard flight management system that can
manage the whole set operation (including takeoff and landing) once the mission is
uploaded.
These levels of autonomy are only related to the basic flying capabilities of the UAV
like take off, landing, cruse, some navigation and not to any other autonomous
function that a UAV might be required like tracking objects, object recognition,
collision avoidance etc. Autonomy of the aircraft has been discussed in detail in the
section 2.2.
2.1.3 Components of a UAV System
A UAV system can be divided into three main components. These will be the UAV
platform, the ground station and the payload (UAVSA c. 2008). These have been
discussed individually below.
Fig. 2.1c Components of a UAV system.
2.1.3.1 UAV Platform
The UAV Platform itself will consist of the following components/systems:
a) The airframe
As mentioned earlier the airframe of a UAV can be of any configuration i.e. fixed-
wing, rotary-wing etc. Like any conventional aircraft the airframe must have the
required aerodynamic properties, be light weight and must be able to sustain the
specified loads for the different application.
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CHAPTER 2: LITERATURE REVIEW
b) The propulsion system
The type of propulsion system used within a UAV will depend on the type of aircraft
and task requirements.
c) Flight control System.
The flight control system (FCS) is the most important system within the UAV. The
system is connected to different types of sensors (gyroscopes, pressure sensors),
navigations systems and avoidance systems. Complexity of the FCS again depends
on the UAV application.
2.1.3.2 Payload
The UAV may be required to carry different types of payloads. One of the most
common payloads is a camera or an optical sensing system. This is usually used by
the operator on the ground station to see were the UAV is going or look at particular
targets. Other payloads can be infrared cameras, radiation detectors, air sampling
systems etc. Military UAVs may have munitions, radars, scanners etc.
2.1.3.3 Ground Control System or Station
At the ground control station the operator controls or monitors the UAV. The ground
station will therefore have avionics flight display, navigation systems, Position
Mapping system, system health monitoring. The Ground Station will also have some
kind of manual control devices like joysticks to control the aircraft. (UAVSA c. 2008)
The Ground Control station will also have system to receive data from the UAV like
video, photographs, etc depending on the onboard systems
2.1.4 Applications
Unmanned Arial Vehicles (UAVs) have seen unprecedented levels of growth in
military and civilian applications domains. UAV applications are usually referred to as
3D or D3, ‘dull, dirty and/or dangerous’. The primary applications identified and used
to date all involve putting the UAV and its payload in environments where the pilot in
a manned operation might be significantly at risk of losing his life or dying of
boredom. Currently the UAV applications are mostly defence related and main
investments are driven by future military scenarios. Today the civilian UAV market is
small compared to the military one. Significant civil markets for UAVs are still to
emerge, with only limited niche applications being currently available. However, in
the next 10-15 years, the expectations for the market growth of civil and commercial
aerial robotics are very high. (Ollero and Manza 2007:3)
There is also a cost justification for using UAVs. They can have longer operational
duration: they can require less maintenance: they can be cheaper on fuel to operate:
they can be operated remotely and sometimes autonomously carrying out the
mission with the minimum of human intervention and supervision: and they can be
deployed in a number of different terrains and are not always dependent on prepared
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CHAPTER 2: LITERATURE REVIEW
runways. Some argue that the use of UAVs in the future will be a more responsible
approach to certain airspace operations from an environmental, ecological and
human risk perspective (UAVSA c. 2008).
Below are some of the examples of UAV applications taken from UAVS website.
Aerial Policeman and Crowd Monitoring
Aerial Reconnaissance
Aerial Traffic and Security Watch
Air to Air Missiles, Air to Ground Missiles, Anti-Tank Missiles
Battlefield Management
Crop Dusting, Crop Management
Disaster damage estimation, Disaster effects management
Fire Fighting
Fishery Protection, Forestry
Geophysical surveys
Guided Shells
Life raft Deployment
Litter on beaches and in parks
Maritime and Mountain Search and Rescue
Mineral exploration
Oil and Gas Exploration and Production
Oil and gas pipeline
Pollution Control and Air Sampling
Search and Rescue
Telecoms relay and signal coverage survey
Waterways and shipping
Wide Area Munitions Deployments
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CHAPTER 2: LITERATURE REVIEW
2.2 Stability and Automation of UAVs
Need for taking control out of the human hands and putting it under some sort of
automatic control has been there since a long time in aviation history. The reason
being that of itself, the path of any aircraft is never stable and aircrafts only neutral
stability in heading. Without control, aircraft tend to fly in a constant turn. In order to
fly a straight and level course continuously-controlling corrections must be made
(McLean 1990). For the human pilot this can be very exhausting and therefore there
is a need for some sort of automatic flight control system (AFCS). In an Unmanned
the need for having some sort of stability devices and AFCS is therefore quite
obvious because an operator on ground will not be able to provide the necessary
control correction will be very difficult.
As mentioned in the previous section UAV can be dived into different categories
based on autonomy they have. This section will have a bit more detail into how
stability and autonomy of UAVs.
a) Stability of un-autonomous UAVs.
An un-autonomous UAV can simply be called a remote control aircraft or a hobby
plane. Some people will argue that such an aircraft cannot be categorised as a UAV
as mentioned section 2.1. The stability of such an aircraft will depend more on the
aerodynamic stability of the airframe. Such stability can be achieved by using
conventional methods like using a dihedral wing for roll stability and positioning the
centre of mass on front of aerodynamic centre for longitudinal stability (Kermode
2006). The ground operators will thus be responsible for manoeuvres and provide
corrections from time to time. The problem in such an aircraft will be that the
increase in aerodynamic stability will mean decrease in manoeuvrability.
b) Stability of semi-autonomous UAVs
In a semi-autonomous UAV the roll of operator is limited to manoeuvres lonely.
Flying the aircraft will be more like playing a video game where the operator can
move around using a joystick and does not have to worry about stabilising or
providing any control corrections. An onboard computer or an autopilot will to this
job. Apart from the aerodynamic stability methods mentioned in previous section
following methods/devices
Aerodynamic Stability Augmentation System (SAS): This system makes
use of the aerodynamic control surfaces like elevators, ailerons and rudders
to provide improved handling qualities (McLean 1990:10). For example for the
pitch stability will be achieved by applying elevator deflections proportional to
the pitch rate which will provide additional damping. Example of such an
autopilot system will be in Chapter 5. This type of systems will require
gyroscopes to record the changes and provide feedback to the autopilot.
Non-Aerodynamic Stability Augmentation Systems: Non-aerodynamic
augmentation devices are used mostly for small and miniature UAVs. Such
devices are used because adverse meteorological conditions generally affect
smaller aircraft more strongly than they affect larger aircraft and there is no
8
CHAPTER 2: LITERATURE REVIEW
known way to create controlled aerodynamic forces sufficient to counteract
the uncontrollable meteorological forces on miniature aircraft. Such systems
can use devices like telescopic shafts with a mass pod or counter weight at
the end. The telescoping shaft and mass pod are stowed in the rear of the
aircraft. When deployed, they extend below the aircraft. (Langley Research
Centre 2005) A similar example of such a system can be of the long rod or
shaft that a funambulist uses while tightrope walking to balance himself.
c) Fully autonomous UAVs
A fully autonomous UAV will have AFCS or autopilot that completely replaces the
human operator in the control of the aircraft. Such AFCS will be capable of take off,
landing, following a navigation path and depending on the specification able to
perform non-aggressive and aggressive manoeuvres. The components and sensors
with fully autonomous UAV will include gyroscopes, pressure sensors, GPS
navigations system, collision avoidance system and electronic compass. The aircraft
will uses similar methods of stability as mentioned earlier.
Table 2.1 shows a list of commercially available systems autopilot system for UAVs.
Table 2.1 List of Commercially Available Autopilots (UAS Research 2008)
Company Autopilot Models Used on website
A Level Aerosystems (Russia) Autopilot A Level Aerosystems, Russia www.zala.aero
RQ-2A/B Pioneer (Pioneer Inc., USA)
MIAG BQM-74 (Northrop Grumman, USA)
BAE Systems (USA) www.baesystems.com
NSU CL327 (Bombardier, Canada)
Mirach100/5E (Galileo Avionica, Italy)
Curtiss Wright - Vista Controls
Global Hawk (Northrop Grumman, USA) www.cwfc.com
Vista Controls Corp (USA) IMMC
Autopilot I Cabure, Yagua (Nostromo, Argentina)
Mavionics (Germany) www.mavionics.de
Autopilot II Yarara (Nostromo, Argentina)
Scarab (SCR, Spain)
X-Vision (SCR, Spain)
Boomerang (BlueBird Aero, Israel)
MicroPilot (Canada) MP2028 www.micropilot.com
Blueye (BlueBird Aero, Israel)
ALBA (INTA, Spain)
Casper (Becker Avionics, Israel)
Rockwell Collins, Inc (USA) G-311 Sky-X (Aliena Aeronautica, Italy) www.rockwellcollins.com
Selex Sensors & AS (UK) Selex FCS Phoenix (BAE Systems, UK) www.selex-sas.com
Scorpio (EADS, France)
Copter I (SurveyCopter, France)
APID (CybAero, Sweden)
wePILOT 1000
DRAC (EADS, France)
weControl (Switzerland) wePILOT 2000 www.wecontrol.ch
DVF 2000 (SurveyCopter, France)
wePILOT4RMAX
Skeldar (Saab, Sweden)
Tracker (EADS, France)
RMAX (Yamaha, Japan)
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CHAPTER 2: LITERATURE REVIEW
2.3 Dynamics of Flight
2.3.1 Introduction
In the previous section it was said that the reason why Autonomous Flight Control
Systems were used in aircrafts was to keep the aircraft stable and under control.
This section is gives some background information about to flight dynamics as it is
directly related to control an stability of a aircraft and thus links up with the
discussion about the autonomous flight controls
2.3.2 Six Degrees of Freedom (6DOF)
An aircraft has got six degrees of freedom in other words it can move in three
directions along three axes (up/down, forward, backward, lift, right) and rotate in
three directions around the three axis (pitch, roll and yaw).Figure 2.3a shows the
6DOF in a body axis system and also shows the conventional nomenclature for
different forces, velocities and moments.
Figure 2.3a Six degrees of freedom of an aircraft in body axis system
(McLean 1990:17)
Stability or the lack of it is a property of an equilibrium state. The equilibrium is stable
if, when the body is slightly disturbed in any of its degrees of freedom, it returns
ultimately to its initial state. An aircraft which may be stable with respect to one
degree of freedom but unstable with respect to another (Etkin 1996). Therefore
based on the inherent stability of the aircraft and AFCS does not to control all the
degrees of freedom. And for this reason autopilots used on an aircrafts can be one-
axis, two-axis or three axes.
2.3.3 Pitch dynamics and Longitudinal Stability
One of the aims set for the project was to look into pitch control of the UAV and
therefore it is important to give some brief background to pitch dynamics. The pitch
of the aircraft is controlled by the elevators. Any deflection on the elevator will
change the pitch of the aircraft. The aircraft usually oscillates at this point before
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CHAPTER 2: LITERATURE REVIEW
settling on the new pitch angle. The change in pitch can also be induced by
activation of high lift devices like flaps, movement of centre of gravity or external
forces and turbulence. There are types of oscillation around the longitudinal axis.
a) Short Period Pitching Oscillations
The short period pitching oscillations is a damped oscillation about the pitch
axis. Whenever the aircraft is disturbed from its pitch equilibrium the mode is
excited ad manifested itself as an oscillation in which the principal variables
are pitch rate and angle of attack. Typically the frequency of the mode is 0.5
to 2 Hz. In manned aircraft, this is in the region of a human pilot natural
frequency, therefore it is essential that the short period mode should be well
damped, otherwise severe handling problems can arise (NFTC 2007:22). For
computer controlling a UAV will usually be capable to handle a higher
frequency but it still needs to be damped as it will damage the onboard
systems or payload. It is the short period oscillation which recovers the angle
of attack to its trim value, and this happens sufficiently quickly that the speed
remains substantially constant.
b) Long Period Pitch Oscillations
The long period pitch oscillations, also known as phugoid oscillations, is the
most commonly seen as a lightly damped low frequency oscillation in speed,
which couples with height. Whenever the aircraft is disturbed from trim speed,
the mode manifests itself as a sinusoidal oscillation in which the principal
variables are pitch attitude and speed changes. A significant feature of the
mode is the angle of attack remains substantially constant throughout. Thus
the change in pitch attitude gives a corresponding change in flight path angle,
and hence the height excursions. The period is long, typically in the band of
40 to 100 seconds, and the damping mainly due to the rate of change of drag
of the aircraft whit speed change. I is possible to deduce that the period of the
mode is determined most entirely by the datum speed, and a good
approximation is that the period is seconds is equal to 0.25 of the true
airspeed in knots (NFTC 2007:23). Since the phugoid mode has such a low
frequency, it poses an undemanding task, and an AFCS can control the mode
even when it is unstable. The phugoid manifests itself as a trimming problem,
which, although not regarded as hazardous when poorly damped however it
will hinder the UAV applications like taking images, sensing or tracking a
target.
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CHAPTER 2: LITERATURE REVIEW
2.4 Modelling and Simulation
2.4.1 Introduction
Modelling and simulations are one of the most important parts of any control system
design and integration. This section gives some background information about
modelling and simulation and how it can be used for UAV systems.
2.4.2 Modelling and Simulation techniques
In order to understand the behaviour of a system, mathematical models are needed.
These models are equations which describe the relationship between the inputs and
output of a system. The basis for any mathematical model is provided by the
fundamental physical laws that govern the behaviour of that system (Bolton
2003:185). For an aircraft the basis of the model will be the relationship between
different Newton’s Laws and Aerodynamic laws that define the motion of an aircraft.
As said in the previous section an aircraft has got six degrees of freedom. This
makes the mathematical model of the aircraft very complex and will take a lot of time
and effort to put all the relationships together. It is therefore important to set of
conditions and assumptions which will define the boundary of the system. For
example with the mathematical modelling of the aircraft a simpler model can be
made by considering only three degrees of freedom or even just two degrees of
freedom. This would make the equations much simpler.
Another important thing to know in modelling is that the equations will include
different constant values or coefficients which are set for the physical system. These
coefficients are needed to be determined for the model to represent the true system.
For example with a simple spring mass model it is important to know the spring
coefficient and the mass for the model to truly represent the system. For an aircraft
these can be different aerodynamic coefficient like lift coefficient, drag coefficient etc.
These coefficients may be determined by doing measurements and calculations on
the actual system, by experimentation or even by simulations that used a different
set of data. For an aircraft this might mean doing wind tunnel tests or CFD tests.
Simulation is the process in which a range of inputs are put through the
mathematical model and the outputs would show the behaviour of the system. Once
the model has been verified it can be used for designing the controller and for
predicting the actual model.
Modelling and simulations are usually done with aid of computer packages. Table
2.4a lists some of the modelling tools that are available for aerospace applications.
2.3.3 Applications
As mentioned in the beginning modelling and simulations are a very important part of
control system designs. These can also be used to investigation behaviour of
systems for optimisation or proving a new concept without risking a real system.
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CHAPTER 2: LITERATURE REVIEW
Table 2. List of Flight Modelling and Simulation tools
Package Description
Merlin Flight Simulator Commercially available flight simulator that enables
the user to configure their own aircraft models for
simulation.
X-plane This is a flight simulator package which enables
users to configure their own aircrafts. This program
can run on and PC
JSB Sim This is another flight simulator package with user
definable aircrafts. It’s an open source software and
therefore will enable to the user to make changes
and even change the working of the simulations
YS Sim This is another flight simulator package with user
definable aircrafts. It’s an open source software and
therefore will enable to the user to make changes
and even change the working of the simulations
Matlab This is a very powerful mathematical computational
package which is widely used for modelling and
control related applications
Simulink Part of Matlab this package enables modelling a
system with the help of GUI blocks
AeroSim Blockset This package working using Simulink and is
designed for aerospace applications and modelling.
Aerospace Blockset This package working using Simulink and is
designed for aerospace applications.
2.3.4 Problems with modelling
A model is defined by assumptions about the real system and therefore can never be
hundred percent accurate. These assumptions can also include the different
coefficients used for the modelling and without the right values the model will be way
off form the real system. In order to get more accurate results a more complex model
will be required. The problems in doing so will be that a complex model will require
more computation and might cause delay when used in control systems.
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CHAPTER 2: LITERATURE REVIEW
2.5 System Identification and control
2.5.1 Introduction
System Identification is the a method of developing a model from a real system in
which tests are used to determine the response from the system to some input, e.g.
a step input and then finding a model that fits the response (Bolton 2003:240).
2.5.2 System Identification tools
Different software packages can be used for system identification some of these are
listed in Table 2.5a
Table 2a. List of System Identification Software packages
Package Description
Matlab A very powerful computational tool with may system
identification functions
Simulink Part of Matlab this package enables modelling a
system with the help of GUI blocks
System Identification Toolbox This is a Matlab/Simulink model used for system
identification
SIDPAC This is a Simulink block set used specifically for
aircraft system identification.
These tools can be used to analysis the outputs for the system on step-response
plots, bode plots and root locus plots.
14
CHAPTER 3: UAV PLATFORM
CHAPTER 3: UAV PLATFORM
3.1 Introduction
There were two UAV platforms that were planned to be used for this project. One
was built as a test plane for 2008 UAV built projects and the second one was to be
built for the 2009 UAV projects. The second one was to be constructed with the help
of other students working on other aspects of UAV project.
3.2 Test Plane
The test plane is a high wing Clipped Wing Taylorcraft ARF model aircraft. The
aircraft had been chosen for its stability and enough space for the payload (Castle
2008:37). The test plane had been flown by the 2008 UAV Project students using
remote control and therefore aim was to use the test plane for the testing of autopilot
and initial modelling for 2009 UAV projects as well.
Figure 3.2a Top Gun Clipped Wing Taylorcraft from Hanger-
9 (Hanger-9 2008)
3.2.1 The Airframe
The dimensions of the airframe are given in the table below.
Table: Speciation of the Test Plane
Wing span 1.07 m
Wing Area 0.428 m2
Length 1.485 m
Weight 6 kg approx
3.2.2 Propulsion Unit and Speed Controller
The aircraft uses an ‘AXi 5330/18 Gold Line’ electric motor with radial mounted
propeller holder (see figure 3.2b). The motor uses two FlightPower EON28 11.1 LiPo
batteries. The output is controlled through a Jeti ADVANCE 90 plus controller.
15
CHAPTER 3: UAV PLATFORM
Figure 3.2b (Model Motors 2006)
Table 3.2a
AXi 5330/18 Gold Line
Specification (Model Motors 2006)
No. of cells max 32
max. 10s Li-Poly
RPM/V 259 RMP/V
Max. efficiency 90%
Max. efficiency current 25 - 60 A (>85%)
No load current / 10 V 2A
Current capacity 75 A/60 s
Internal Resistance 32 m
Dimensions (Diameter x Length) 63 x 64 mm
Shaft diameter 8 mm
Weight with cables 652 g
16
CHAPTER 3: UAV PLATFORM
Table 3.2a
Jeti ADVANCE 90 plus controller Specifications
(Jeti 2005)
Dimensions: 65 x 55 x 17 mm
Weight: 75/90 g
Continuous current: 90 A
Accu NiXX / LiXX: 14-32 / 5-10
Voltage 15 – 42 V
Figure: 3.2c Jeti Advance 90 plus speed
controller.
3.2.3 Control system
PCM9X RS10DS.
The aircraft is manually controlled by PCM ii Transmitter via RS10DS The aircraft
has got four servos which control the ailerons, elevators and rudder.
JR PCM9X ii Transmitter JR RS10DS Receiver
Figure: Manual control unit
MicroPilot
The aircraft is autonomously controlled by Micro ilot MP2028g autopilot. Details
about the autopilot are given in Chapter 4.
3.2.4 Power supplies
The aircraft has got separate power supply autopilot, servos and the motor.
3.2.5 Work done on test plane
The test plane had been assemble by the 2008 Project students but there were
asks
some of the tasks required to make the aircraft airworthy
• systems.
Installation of remote control receiver, autopilot and other systems
• Measurement of the aircraft for modelling and simulation.
17
CHAPTER 3: UAV PLATFORM
3.3 UAV 2009 Platform
3.3.1 The Airframe
Figure 3.3a below show the dimensions for the aircraft. The airframe was designed
by other students working on the UAV project. The aircraft was still under
construction at the time of this report being written.
Figure 3.3a Pheonix 09 UAV designed by M. E .Bahrami
18
CHAPTER 3: UAV PLATFORM
Figure 3.3b UAV fuselage under construction.
3.3.2 Propulsion Unit and Speed Controller
Same as the test plane. See section 3.2.2
3.3.3 Control system
Same as the test plane. See section 3.2.3
3.3.4 Power Supply
Same as the test plane. See section 3.2.4
3.3.5 Other components
An extra servo will be used to unlock and drop the flaps.
19
CHAPTER 4: AUTOPILOT
CHAPTER 4 AUTOPILOT
4.1 Introduction
The autopilot used for the UAV is a MicroPilot MP2028g. The autopilot is capable of
flying the UAV fully autonomously. The autopilot uses gyroscope, air pressure and
GPS as senses for inertia, speed, altitude and position to control the aircraft. During
the project the autopilot been tested on ground but a flight test could not be
achieved.
4.2 Components
The MicroPilot MP2028g autopilot system consists of the following components.
Table 4a: List of components for autopilot system
Component Description
MP2028g CORE
This is the main autopilot board and all the other
components are connected to it.
Figure 4.2a (MicroPilot 2004)
MP2028g AGL
Above Ground Level (AGL) is an ultrasonic altimeter
that provides altitude information to an altitude of
about 4.88m above the ground. It is required for
autonomous takeoff and landing.
Figure 4.2a (MicroPilot 2004)
20
CHAPTER 4: AUTOPILOT
MP-Servo board
The Servo board distributes the servo signal to each
servo
Figure 4.2a (MicroPilot 2004)
MP-ANT
This is the GPS antenna which connects to the
CORE board. The antenna is mounted on a 10cm x
10cm copper board.
Figure 4.2a (MicroPilot 2004)
Radio Modems and MP-COM board
COM
The radio modem connects to the ground station
computer and communicates with the autopilot via
the COM board.
Figure 4.2a
Faraday Cage
The Faraday cage had been designed by 2008 UAV
Project Students to shield the CORE board from any
external interference especially from the motor.
Figure 4.2a
21
CHAPTER 4: AUTOPILOT
Software The software is used to communicate with the
autopilot from the ground station.
MicroPilot Horizon:
This software provides a GUI for configuring the
autopilot and setting up flight path.
Microsoft HyperTerminal:
The HyperTerminal can be used to communicate
with the autopilot. It uses a commend line
setting
interference but will enable to configure more set
and acquire flight data.
4.3 Installation
The autopilot components were installed on the control board. In this section only the
important points to be remembered while installing the MP2028g is mentioned. Full
details of installing MP2028g can be found MicroPilot Autopilot Manual and
Installation DVD.
a) Control Board
All the autopilot components are installed on a single board. The layout of the control
board for the test aircraft is shown in figure 4.3a
Figure 4.3a: Autopilot Board for Test Plane.
b) Servo Board
22
CHAPTER 4: AUTOPILOT
The servo board was connected to the servos for normal setting. This means that
only servos for ailerons, elevators, rudder and throttle were connected. Figure 4.3b
below shows which pins are supposed to be connected to which servo.
Figure 4.3b: Servo Board
4.4 Configuration
The autopilot was configured using the MicroPilot Horizon software. It was
configured for Normal settings and under a fake GPS lock.
The autopilot was then tested on ground for basic servo responses.
4.5 Problems with the autopilot
There were some issues with configuration the autopilot
a) Communication Problem
The autopilot should be able to communicate with the ground station either by using
MicroPilot Horizon or by using Microsoft HyperTerminal. The autopilot was able to
communicate with the Horizon software properly most of the time but it did freeze the
computer while configuring the Rudder setting couple of times. This behaviour
however only happened while using the personal laptop and did not occur when
universities laptop was used. This might have happened have happened due to the
former being too slow.
The main communication problem occurred when HyperTerminal was used to
communicate with the autopilot. The HyperTerminal only communicated once and for
other attempts showed nonsense values on the screen as shown in figure 4.5.
The communication using HyperTerminal is very important to get the flight data for
any further investigation. Most importantly the data is very important for analysis for
selection of proper gains.
23
CHAPTER 4: AUTOPILOT
Figure 4.5a Screenshots of the HyperTerminal data. Top: The data on the HyperTerminal screen
when a proper connection was estabilished. Above: The HyperTerminal data showing nonsense
values.
b) Battery problem:
The autopilot seems to drain the batteries in a very short period of time and this
delayed configuring it. However with the new batteries this did not seem to be a
problem.
The autopilot had some issues with the AGL unit in the 2008 UAV project. However
the AGL seem to respond properly during the ground tests showing the right
distance from ground. It might be possible that the interference from the motor would
have affected the AGL unit in the past.
24
CHAPTER 5: FLIGHT SIMULATION
CHAPTER 5: FLIGHT SIMULATION
5.1 Introduction
The UAV was planned to be simulated using Merlin Flight Simulator present at
Coventry University’s Aerospace Lab. The objective behind doing so was to
understand the stability of the aircraft so that the proper gains for the MicroPilot
MP2028g can be determined without risking the UAV in a real flight test. In order to
do this it was important to understand the working of Merlin Simulator1 and its own
Arthur Autopilot.
5.2 Merlin Flight Simulator
5.2.1 Simulator Choice
There were two flight simulators available for the simulations, Merlin’s MP520 and
MP521. Some of the options available on the two can be seen in Table 5.2a.
Table 5.2a Merlin Flight Simulators present at Coventry University.
Merlin MP520 Merlin MP521
Excalibur I
Aircraft Config. Software Excalibur I
Excalibur II (beta)
Aircraft Systems
Autopilot Arthur
Flight Controls Systems
Motion base actuators Electric Hydraulic
Because no autopilot was present on MP520 it was initially decided to use MP521
for the simulations. However MP520 could still be used if the autopilot was not
needed for the particular flight and if the model was not for Excalibur II format.
5.2.2 Aircraft Configuration Software
There were two aircraft configuration software available with MP521, the Excalibur I
(Ex-I) and Excalibur II (Ex-II). Excalibur I is a stable version and also works on
MP520. However the aircraft model designed using Excalibur I is very simple and it
does not provide options for advance design like multiple section wing, horizontal
and vertical panels.
MP521 had beta version of Excalibur II. This version does provide advance
configuration. During the initial stage of the project Ex-II was used to configure
25
CHAPTER 5: FLIGHT SIMULATION
aircraft models but due to some problem the models did not work or were unstable.
These issues were reported to Merlin. Another problem with Ex-II was that it could
not be installed on any other computer which meant that the aircraft needed to be
configured in lab only. Therefore it was decided to use Ex-II only and keep the
models simple.
5.2.3 Autopilot
The MP521 simulator has software autopilot installed on it called Arthur. Arthur is a
4-axis (roll, pitch, yaw and altitude) autopilot which means it can be used for fixed
wing as well as rotary wing aircrafts. The cockpit controller deflections (from. pitch
and roll stick, Yaw pedals and throttle lever) are mixed with autopilot servo deflection
to provide closed-loop control. (Merlin Products 2007)
5.2.3.1 Control Modes
Arthur provides control using five modes. Figure 5.2a shows the Control Panel inside
the simulator cockpit to control the autopilot. It also shows the backend for Arthur
which shows the current status of the autopilot and can also be used to set gains for
the different modes
1.) Stability Augmentation System (SAS) Modes
The stability augmentation seeks to provide handling qualities in roll, pitch and
yaw by providing additional damping. For example for the pitch stability this is
achieved by applying a control surface deflection proportional to the pitch rate.
It is important to engage the SAS Modes before any other autopilot modes
can be used.
2.) Autopilot (AP) Modes
The AP modes maintain a particular flight parameter. For example for the
Altitude (ATT) mode the autopilot will maintain the aircraft at a specific pitch
altitude. ATT mode will either maintain the current altitude when the mode is
engaged or will move the altitude set in command mode.
There are three modes available under AP mode:
a) Altitude (ATT) mode
b) Wing Leveller (WNG LVL) mode
c) Turn Co-Coordinator (TC) mode
26
CHAPTER 5: FLIGHT SIMULATION
Figure 5.2a Merlin Flight simulator Autopilot: The Flight Control Panel and Arthur backend.
3) Command (CMD) Modes
The CMD modes are used to set the demands for AP mode. For example the
Altitude hold mode will be used to set the required altitude and vertical speed.
The ATT autopilot mode will then try to maintain this altitude.
There are three modes available under CMD mode
a) Heading Hold (HDG) Mode
b) Altitude Hold (ALT) Mode
c) Speed Hold (IAS) Mode
These modes can be engaged only if the related AP modes are engaged first.
4) Navigation (NAV) Mode
Arthur includes two navigation modes for tracking VOR beacons and
instrument landing systems. These modes were not required for this project.
27
CHAPTER 5: FLIGHT SIMULATION
Control Mixing
It is important that the aircraft model has got External
Controls enabled on the system settings of Excalibur
in order for autopilot to engage (see figure 5.2b).
5.3 Flight Simulation Models
In order to understand the working of the flight
pre-built stable model
simulator and Arthur autopilot a pre
of Cessna172 was used. The plan was to modify this
model convert it into the Test Plane model and UAV Figure 5.2b The external Controls
settings must be checked on the
model. Systems settings on the Excalibur
editor for autopilot to function.
One of the issues with the configuring the models
scaled
were the simulator could not run small models and therefore the models were sca
up. Another issue was that Excalibur only as combustion engines as power plant
which means that the total mass of the aircraft will reduce once the consumption of
fuel. One way to overcome this was to use a value of zero for SFC.
5.4 Test Flights
e
The aim of the flight testes was to look into the longitudinal stability of the aircraft.
This meant analysis of the natural short-period oscillations and long- -period (or
Phugoid) oscillations damping of the aircraft and how the autopilot will assist in
further damping.
The tests were done to find the open loop response and close loop response i.e.
when the autopilot was engaged.
5.4.1 Open Loop and Close Loop Response Test
In order to get the open loop response of the aircraft different types of signals were
manually inputted using the control stick.
The closed loop response flight tests were similar to the open loop test the only
these
difference being that the autopilot was switched on for the tests.
One of the main problems encountered during the tests was that a perfect and
repeatable input could not be inputted manually. Another problem for these tests
was that as these were done quite earlier stage in the project getting used to the
ight
flight simulator took some time.
5.4.2 Comparison test
These testers were done in the last stages of the project using Merlin Simulator in
order to see how the different modes available within the autopilot will affect the
ee
stability if flight. For this three flights were conducted. The Cessna 172 model was
used.
28
CHAPTER 5: FLIGHT SIMULATION
a) Autopilot off: For the first test took place in autopilot off. The flight test procedure
is given below
Time (min) Action Comment
00:00 Fly from 609.6m (2000ft) with IAS
129.64 km/h (70 kt)
02:15 Pull stick back for 45 sec Aircraft stalls
03:00 Release stick Wait for aircraft to settle
11:30 Stop. Save as fly1
b) Autopilot on SAS Pitch mode. For this test the autopilot was left on in stability
augmentation mode
Time (min) Action Comment
00:00 Fly from 609.6m (2000ft) with IAS
129.64 km/h (70 kt) SAS mode
engaged
02:30 Pull stick back for 45 sec Aircraft stalls
03:15 Release stick Wait for aircraft to settle
11:45 Stop. Save as fly2
c) Autopilot on in ATT mode. For this test the autopilot was set in ATT mode. The
flight test procedure is given below
Time (min) Action Comment
00:00 Fly from 609.6m (2000ft) with IAS
129.64 km/h (70 kt) ATT mode
engaged
02:15 Pull stick back for 45 sec
03:00 Release stick Wait for aircraft settle
11:30 Stop. Save as fly3
The results for these tests are discussed in next section.
5.5 Results and Analysis
5.5.1 Open Loop and Close Loop Response Analysis
As mentioned section 5.4 these tests were done in the earlier stage of the project.
The full list of test and results can be found in Appendix B.
There was a major problem with these tests because proper input signals could not
be generated and because of the unfamiliarity with the M521 keeping the aircraft in a
straight path was found to be very difficult.
29
CHAPTER 5: FLIGHT SIMULATION
30
Elv Angle
Pitch Angle
X: 43
Y: 20.9
X: 61
20
Y: 17.15
10
0
X: 33
Y: -9.31
-10
-20
X: 28
Y: -28.61
-30
0 10 20 30 40 50 60 70 80 90 100
Figure : Pitch response for a impulse elevator deflection
5.5.2 Comparison test analysis.
5.5.2c
Figure 5.5.2a, 5.5.2b and 5.5.2c show the results from the comparison test in No
. differences
Autopilot Mode, SAS Pitch Mode and AP ATT Mode respectively. The differ
between the three are quite clear from these plots.
5.5.2a:
Figure 5.5.2a Results for the flight without Autopilot.
30
CHAPTER 5: FLIGHT SIMULATION
Figure 5.5.2b: Aircraft flight in SAS Autopilot mode.
Figure 5.5.2c: Aircraft flight in ATT Autopilot mode.
31
CHAPTER 5: FLIGHT SIMULATION
Without the autopilot the elevator deflection looks almost like a square signal which
is maintained at a constant value till the control stick is released. Comparing this with
possible
the SAS Pitch mode plot, it is possible to see deflections even when the control stick
has been held in set position. This is even more visible in the third test when the ATT
mode was engaged on the autopilot. Another difference between the three is the
amplitude and frequency of oscillations in altitude plot of the three tests. The values
for these are given in table 5.5a
Table 5.5a : Results analysis of comparison flight
Control Stick Pulled
No. of Frequency
Amp1 oscillations t1 ω (rad/s) T (sec)
Fly 1 50.5367 3.020134 14.9 0.42169 45
Fly 2 80.8 2.472527 18.2 0.34523 45
Fly 3 48.7 3.020134 14.9 0.42169 45
Control Stick Released
No. of Frequency
Amp2 oscillations t2 ω (rad/s) Ts (sec)
Fly 1 48.6 11 21.1 0.297781 232.1
Fly 2 49.6 10 21 0.299199 210
Fly 3 4.3 5 22.6 0.278017 113
Figure 5.5.2d . Cmparison Test analyis
5.6 Conclusion
There wasn’t much analysis done one the data from the flight simulations because
most of these test were done on C172 model in order to get used to the simulator
and for the actual UAVs the data would be quite different. The results were however
recorded and some examples can be seen in the Appendix B. This was done at an
early stage of the project and it was found that the input signals were making the
aircraft unstable. It was also for that the data was difficult to analyse as the results
were not the perfect step responses which were shown on text books. At that point it
was thought that may be a different package could be used to simul simulate to have more
control over the simulation.
32
CHAPTER 6: SYSTEM IDENTIFICATION
CHAPTER 6: SYSTEM IDENTIFICATION
6.1 Introduction
In order to get more controlled modelling and simulation different options for system
identification tool were researched. Based on the research done U-Dynamics
AeroSim Block set seemed to be a good option to use for both simulation and
system identification.
6.2 Reasons for choosing AeroSim Blockset
The AeroSim seemed to be a very attractive package for modelling and simulation
part of the project for the following reasons:
• AeroSim offered a wide range of complete aircraft models for Simple up to
6DOF Aircraft models (U-dynamics 2008)
• AeroSim could be used on any PC with Matlab/Simulink installed on it. (U-
dynamics 2008). This was very attractive as it meant the data can be
analysed straight after the simulation was done.
• AeroSim offered Visual output to FlightGear Flight Simulator and Microsoft
Flight to simulator. (U-dynamics 2008) The block also included a Cessna 172
model for FlightGear demo. This seemed to be a good feature as same
model had been tested on Merlin Flight Simulator.
• From the research done and looking into different journal articles and
conference papers it was found that AeroSim blockset was used for many
similar projects.
• The blockset was free for Academic and Educational purposes. (U-dynamics
2008)
Based on the above features offered by AeroSim blockset decision to move the
simulations from MP521 to AeroSim for system identification was taken.
6.2 Aircraft model configuration problem with AeroSim
This was the main problem with using the blockset. The aircraft configuration model
for AeroSim was very complex compared to the models used previously. It required
the many aerodynamic coefficients which were not used for any of the previous
models and therefore were not know. For example the Lift coefficient as a sum of
many other coefficients as shown in the equation below.
To determine the coefficients required much deeper understanding of aircraft
aerodynamics. The other problem was that to derive these coefficients manually
would take a lot of time and would therefore shift the whole aim of the project.
33
CHAPTER 6: SYSTEM IDENTIFICATION
The block model for the Cessna 172 was completed even the aircraft configuration
was not complete. Figure 6.2a and Figure 6.2b
Figure 6.2a Simulink model designed for C172 using AeroSim Blockset.
Figure 6.2b Response for running the Simulink model
34
CHAPTER 6: SYSTEM IDENTIFICATION
6.3 DDATCOM software package
computational
Research was done to find some kind of computational tool to derive the coefficient.
A software package called DDATCOM was found to be used in some projects that
e coefficients.
could give these aerodynamic coefficients. Data compendium (DATCOM) had been
developed by United States Air Force (USAF) and contained a large collection of
information containing of classical aerodynamics and analysis and experimental
2007).
data. (Jung and Tsiotras 2007) DDATCOM or DigitalDATCOM is a computer
database of this information and uses it on to the aircraft model to determine the
aerodynamic coefficients.
6.3.1 DATCOM modelling
DATCOM used a different set of perimeter for aircraft configuration. In particular it
required coordinates for the shape of the aircraft. In order to do so measurements
were taken from C172 photograph. This can be seen in figure 6.3a.
:
Figure 6.3a: Measurement taken from Cessna 172 photograph (EuroControl, c. 2009) for
DDATCOM.
After taken the measurements data was put into the DDATCOM aircraft configuration
file. Based on this data DDATCOM produced a 3d model of the aircraft as seen in
figure 6.3b
Despite the 3d model looking alright there were some problems within the
configuration which caused error and the results for the model could not be accrued.
The screen shot of the output file are shown in figure 6.3c
35
CHAPTER 6: SYSTEM IDENTIFICATION
Figure 6.3b: DATCom model for Cessna 172
Figure 6.3c Output file from DDATCOM
It wasn’t possible to resolve these errors in the due time. DDATCOM did plot some
graphs which can be found in Appendix B.
36
CHAPTER 6: SYSTEM IDENTIFICATION
6.4 Flight Gear simulation problem
The AeroSim blockset contained an example of a C172 model that would simulate in
Flight gear package, see figure 6.4a. The problem was that the C172 model was
actually in flight gear and therefore could not be used for any other analysis. Also
problems were encountered while trying to use this example. Example can be seen
in 6.4b.
Figure 6.4a C172 model simulation in Flight Gear
Figure 6.4b Error while trying to run Flight gear with AeroSim.
37
CHAPTER 6: SYSTEM IDENTIFICATION
6.5 Conclusion
As can be seen from the previous sections the experience with using the AeroSim
did not go very well and no system identification analysis was done unfortunately.
The models and configuration files can be found in the CD attached with this report.
38
CHAPTER 7: CONCLUSION
CHAPTER 7: CONCLUSION
The aim of this project was to implement and understand the working of MP2028 and
to model and simulate the aircraft and the autopilot. Even though the project did not
go as planned the following can be listed as the achievements or the positive points
of the project.
• Better understanding of aircraft control systems.
• Familiarisation and implementation of the MP2028g autopilot
• Better understanding of working of Merlin Flight simulator
• Knowledge of different packages available for simulation.
However there are some things that the project did not achieve.
• The simulations did not work as planned specially with AeroSim Blockset.
This also ended up in lack of analysis.
• A linearised model of the pitch dynamics was not designed.
• A real flight test did not take place and therefore no real data could be
acquired for further analysis.
The move to use AeroSim Blockset made the simulation side of the project more
complicated. Also not getting to fly the test plane according to plan was also a de-
motivation. If flown the data from the aircraft would have been good for comparison
for simulations and broadened the analysis. There was a very useful knowledge
gained during the project though and therefore if the project was run again the use of
AeroSim Blockset will still be considered but this time he models would be designed
specifically for the blockset rather than adapting or converting the models for other
packages.
39
CHAPTER 8: FURTHER W ORK AND RECOMMENDATIONS
CHAPTER 8: FURTHER WORK AND RECOMMENDATIONS
There is a lot of potential work for continuing and improving all aspects of this
project.
The autopilot has not been used in a real flight till now and therefore the full potential
of the autopilot has not been tested till date. Therefore there is still some work that
can be done in this area.
As seen in the report the major problems were related to simulations. It would be
recommended to install Matlab/Simulink on the Merlin Simulators. This can be used
for more controlled simulations and analysis of aircraft models. It might be possible
to integrate the models with AeroSim Blockset.
All the open source and freeware software like DDATCOM, Flight Gear, and
AeroSim has been included in the project and would help further work related to a
similar project.
40
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