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. NOTE: I am putting this online just to give the undergraduate students an example of a final year dissertation. Please do not copy as it will be considered plagiarism by your university.
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. 1 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. 2 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 220.127.116.11 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. 3 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) 4 CHAPTER 2: LITERATURE REVIEW 18.104.22.168 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. 22.214.171.124 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. 5 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. 126.96.36.199 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. 188.8.131.52 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 6 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 7 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) 9 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 10 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. 11 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. 12 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. 13 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) 184.108.40.206 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 REFERENCES REFERENCES BBC News (2009) Robot planes take to the skies [online] available from <news.bbc.co.uk/2/hi/technology/7938522.stm> [12 March 2009] Becker Avionics (2006) Casper 250 Manual [online] Becker Avionics. Available from <http://www.beckerusa.com/products/images/pdfs/Becker%20Casper%20250%2 0Manual.pdf> [28 Oct 2008] Beggs, B. (2009) ‘BAE Systems: Tornado to Typhoon & UAV’. Royal Aeronautical Society Lecture delivered on 21 January 2009 at Coventry University Techno Centre Castle, R. (2008) UAV Built Project 2008. Unpublished dissertation. Coventry University. Etkin, B. & Reid, L. D. (1996) 3rd edn. Dynamics of Flight. USA: John Wiley & Sons, Inc. EuroControl (c. 2009) Aircraft Performance Database V2.0 [online] available from <http://elearning.ians.lu/aircraftperformance/Default.aspx> [31 Jan 2009] Hanger9 (2009) Clipped Wing Taylorcraft ARF (HAN1850): Hangar 9 [online] available from <http://www.hangar- 9.com/Products/Default.aspx?ProdID=HAN1850> [March 2009] Jeti (2005) Jeti Model ADVANCE 90 plus [online] available from <http://www.jetimodel.cz/eng/hlavnien.htm> [Dec 2008] Jung, D. ; Tsiotras, P. (2007) 'Modelling and Hardware-in-the-Loop Simulation for Small Unmanned Arial Vehicle.' Proceedings from AIAA Infotech@Aerospace 2007 Conference held May 7-10 2007 in California. AIAA 2007-2768, Available from <www.ae.gatech.edu/people/ptsiotra/Papers/infotech07b.pdf> [03 Feb 2009] Kermode, A.C. (2006) 11th edn. ed. by Barnard, R.H. & Philpott, D.R. Mechanics of Flight. Harlow: Pearson Education Limited McLean, D. (1990) ed. by Grimble, M.J. Automatic Flight Control Systems. UK: Prentice Hall International Ltd. Merlin Products (2007) Arthur Autopilot User Manual, UK: Merlin Products. MicroPilot (2004) MicroPilot Installation Video [DVD] Canada: MicroPilot Model Motors (2006) AXI 5330/18 GOLD LINE [online] available from <http://www.modelmotors.cz/index.php?page=61&product=5330&serie=18&line= GOLD> [12 Dec 2008] MSN Encarta (2008) Unmanned Aerial Vehicle [online] available from <http://encarta.msn.com/encyclopedia_701610394/Unmanned_Aerial_Vehicle.ht ml> [27 Oct 2008] Northrop Grumman (2007a) RQ-4 Block 20 Global Hawk [online] available from <http://www.is.northropgrumman.com/systems/ghrq4b.html> [14 March 2009] Northrop Grumman (2007b) MQ-8B Army Fire Scout [online] available from <http://www.is.northropgrumman.com/systems/mq8bfirescout_army_gallery.html > [14 March 2009] Ollero, A; Manza I (2007) 'Introduction' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 1 Raptis, I. A. ; Valavanis, K. P. (2007) 'Airplane Basic Equations of Motion and Open-Loop Dynamics.' In Advances in Unmanned Arial Vehicles. ed. by Valavanis, K. P. The Netherlands: Springer: 49 41 REFERENCES Remub, V. ; Deeg, C. ; Musial, M. ; Hommel, G. ; Cuesta, F. ; Ollero, A. (2007) 'Autonomous Helicopters.' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 111 UAS Research (2008) ‘UAS Yearbook 2008/2009’ [online] USA: University of North Dakota. Available from < http://www.uasresearch.org/home/default.asp?L1=15&a=86> [11 Nov 2008] UAVSA or Unmanned Aerial Vehicle Systems Association (2008) Unmanned Aerial Vehicle Systems Association What is a UAV? [online] available from <http://www.uavs.org/index.php?page=what_is> [27 Oct 2008] US OSD (2005) ‘Unmanned Aircraft Systems Roadmap 2005-2030’ [online] USA: Office of Secretary of Defence. Available from <www.fas.org/irp/program/collect/uav_roadmap2005.pdf> [03 Mar 2009] 42 BIBLIOGRAPHY BIBLIOGRAPHY Beggs, B. (2009) ‘BAE Systems: Tornado to Typhoon & UAV’. Royal Aeronautical Society Lecture delivered on 21 January 2009 at Coventry University Techno Centre Etkin, B. & Reid, L. D. (1996) 3rd edn. Dynamics of Flight. USA: John Wiley & Sons, Inc. Garnell, P. & East, D.J. (1977) Guided Weapon Control Systems. UK: Pergamon Press Jeti (2005) Jeti Model ADVANCE 90 plus [online] available from <http://www.jetimodel.cz/eng/hlavnien.htm> [Dec 2008] Jung, D. ; Tsiotras, P. (2007) ‘Modelling and Hardware-in-the-Loop Simulation for Small Unmanned Arial Vehicle.' Proceedings from AIAA Infotech@Aerospace 2007 Conference held May 7-10 2007 in California. AIAA 2007-2768, Available from <www.ae.gatech.edu/people/ptsiotra/Papers/infotech07b.pdf> [03 Feb 2009] Kermode, A.C. (2006) 11th edn. ed. by Barnard, R.H. & Philpott, D.R. Mechanics of Flight. Harlow: Pearson Education Limited Manai, M. ; Desbiens, A. (2005) 'Identification of a UAV and Design of a Hardware- in-the-Loop System for Nonlinear Control Purpose' Proceedings from AIAA Guidance, Navigation, and Control Conference and Exhibit held Aug 5-18 2007 in California. AIAA-2005-6483, Available from <w3.gel.ulaval.ca/~desbiens/publications/IdentificationUAVHardwareInTheLoop. pdf > [19 Feb 2009] McLean, D. (1990) ed. by Grimble, M.J. Automatic Flight Control Systems. UK: Prentice Hall International Ltd. MSN Encarta (2008) Unmanned Aerial Vehicle [online] available from <http://encarta.msn.com/encyclopedia_701610394/Unmanned_Aerial_Vehicle.ht ml> [27 Oct 2008] NFTC or National Flying Laboratory Centre (2007) Flight Laboratory Course for Coventry University. Unpublished booklet. UK: Cranfield University. Ogata, K. (2002) 4th edn. Modern Control Engineering. USA: Prentice-Hall, Inc. Raptis, I. A. ; Valavanis, K. P. (2007) 'Airplane Basic Equations of Motion and Open-Loop Dynamics.' In Advances in Unmanned Arial Vehicles. ed. by Valavanis, K. P. The Netherlands: Springer: 49 Remub, V. ; Deeg, C. ; Musial, M. ; Hommel, G. ; Cuesta, F. ; Ollero, A. (2007) 'Autonomous Helicopters.' In Multiple Heterogeneous Unmanned Arial Vehicles. ed. by Ollero, A. & Maza, I. Germany: Springer-Verlag: 111 UAS Research (2008) ‘UAS Yearbook 2008/2009’ [online] USA: University of North Dakota. Available from < http://www.uasresearch.org/home/default.asp?L1=15&a=86> [11 Nov 2008] US OSD (2005) ‘Unmanned Aircraft Systems Roadmap 2005-2030’ [online] USA: Office of Secretary of Defence. Available from <www.fas.org/irp/program/collect/uav_roadmap2005.pdf> [03 Mar 2009] I
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