This document discusses control approaches for cooperative unmanned aerial vehicles (UAVs). It first presents the modeling of a quadrotor's dynamics using piecewise affine systems to capture nonlinearities. It then describes the design of an experimental quadrotor platform called UPATcopter that can estimate its state autonomously. Finally, it proposes three control strategies for quadrotors: 1) a constrained finite time optimal controller for attitude control, 2) a switching model predictive controller for trajectory/attitude control, and 3) a PID-2nd derivative controller for attitude and translation control. Experimental results demonstrate the effectiveness of these control approaches.
Presentation given during ICRA 2013 to accompany the following paper: C. Papachristos, K. Alexis, A. Tzes โModel Predictive Hovering-Translation Control of an Unmanned Tri-TiltRotorโ, IEEE International Conference on Robotics and Automation, ICRA 2013, Karlsruhe, Germany
Automated Verification of an Onboard Mission Planning and Execution System fo...Florian-Michael Adolf
ย
Automated mission planning is one of the key components of an autonomous UAV. The software validation and verification for such decisional autonomy functions is a challenging problem. The software component includes the closed loop vehicle control as well as environment perception. As this is a safety-critical software component, it is important that this software works safely and within projected performance boundaries. This paper discusses the verification and validation approach for the sampling-based mission planner of an unmanned rotorcraft. A layered test strategy is presented, which utilizes different testing methods that complement and build upon each other. Its strengths as well as the possible improvement directions of this approach are discussed. An emphasis is given on automated software-in-the-loop simulations. The approach additionally utilizes benchmarks to assess the implementation performance and real time properties. Finally, to be able to assess the overall test quality, a set of different scalable test abstractions (SUT size, test effort, level of automation, coverage, test complexity and feedback time) is used to analyze the presented strategy.
The present research is due to study the performance of
engine-propeller cells to be used in the design of a Micro
Air Vehicle (MAV). MAV design conditions: weight less than 200gr, maximum size 30cm, to fly a distance of 200m, and to be able to carry a camera and chemical sensors.One of the goals of the study is to use commercial parts (engines and propellers) in order to reduce manufacturing cost. The experiments are made in a subsonic open-circuit wind tunnel. The results are the aerodynamic drag coefficient of the propeller-engine cell (engine off), the static thrust test realized with engine on and tunnel off, at different RPM and the dynamic thrust test with engine and tunnel on, at different
RPM and different tunnel flow velocity.
Presentation given during ICRA 2013 to accompany the following paper: C. Papachristos, K. Alexis, A. Tzes โModel Predictive Hovering-Translation Control of an Unmanned Tri-TiltRotorโ, IEEE International Conference on Robotics and Automation, ICRA 2013, Karlsruhe, Germany
Automated Verification of an Onboard Mission Planning and Execution System fo...Florian-Michael Adolf
ย
Automated mission planning is one of the key components of an autonomous UAV. The software validation and verification for such decisional autonomy functions is a challenging problem. The software component includes the closed loop vehicle control as well as environment perception. As this is a safety-critical software component, it is important that this software works safely and within projected performance boundaries. This paper discusses the verification and validation approach for the sampling-based mission planner of an unmanned rotorcraft. A layered test strategy is presented, which utilizes different testing methods that complement and build upon each other. Its strengths as well as the possible improvement directions of this approach are discussed. An emphasis is given on automated software-in-the-loop simulations. The approach additionally utilizes benchmarks to assess the implementation performance and real time properties. Finally, to be able to assess the overall test quality, a set of different scalable test abstractions (SUT size, test effort, level of automation, coverage, test complexity and feedback time) is used to analyze the presented strategy.
The present research is due to study the performance of
engine-propeller cells to be used in the design of a Micro
Air Vehicle (MAV). MAV design conditions: weight less than 200gr, maximum size 30cm, to fly a distance of 200m, and to be able to carry a camera and chemical sensors.One of the goals of the study is to use commercial parts (engines and propellers) in order to reduce manufacturing cost. The experiments are made in a subsonic open-circuit wind tunnel. The results are the aerodynamic drag coefficient of the propeller-engine cell (engine off), the static thrust test realized with engine on and tunnel off, at different RPM and the dynamic thrust test with engine and tunnel on, at different
RPM and different tunnel flow velocity.
Final presentation by University of Alabama in Huntsville at CanSat 2008
http://www.astronautical.org/2008/06/15/cansat-2008-university-of-alabama-in-huntsville/
Bioracermotion aero virtual wind tunnel. Bringing the wind tunnel to your living room. Learn and train your body to become faster with more sustainable power. Contact our team today and become faster tomorrow info@bioracermotion.com
The Centurion Orbit Transfer Vehicle (OTV) was part of our Aerospace Engineering Senior Design project at the University of Illinois at Urbana-Champaign. It is equipped with the latest technologies, including a nuclear thermal propulsion system. The structure weighs 89,000 kg and is capable of transporting cargo to Lagrange points L1 or L2.
Aerodynamics of flapping wing MAV
The question which I got from the panel was how to calculate the Reynolds number ?..the ans is by claculating MAC Mean Aerodynamic Chord
A Strategy for Reliability Evaluation and Fault Diagnosis of Autonomous Under...Koorosh Aslansefat
ย
Underwater vehicles contribute significantly to exploiting great maritime resources. Autonomous vehicles are one of the various kinds of underwater vehicles which are able to perform operations without operator's interference. Autonomous underwater vehicles can be classified according to their propulsion systems. Autonomous Underwater Gliders (AUG) are among autonomous underwater vehicles which fall under the category of glide type underwater vehicles. They are designed in a way that they benefit low energy consumption and a wide survey range. Their reliable design is one of the challenges facing their manufacturing. Fault tolerance is one of the important attributes in designing reliable systems. Recognizing, evaluating and facing the faults are of great importance in designing fault tolerant systems. This paper studies underwater Glider vehicles' subsystems, considers their faults and causes, and provides a typical fault tree for these vehicles form which glider reliability and the effects of glider subsystems on its failure can be driven.
The Mars Autogyro Neutroscopic Explorer defines a new design โX-Iโ which has been optimised to meet the challenge of the hostile Martian atmosphere. It blends in an autogyro rotor into a delta wing to enhance the lift capabilities of the aircraft in supersonic and sub sonic flight regimes. The diagrams below represent the chronological order in which the design was generated
Calculating Wind Farm Production in Al-Shihabi (South Of Iraq) Using WASPIJERA Editor
ย
The Wind Turbine farms are becoming popular in the renewable energy world. In this research, the Wind Atlas
Analysis and Application Program (WAsP) has been used to estimate wind power density in Al-Shihabi (south
of Iraq). All statistical operations on data series are obtained from Field data collected from the wind
measurement towers which installed by the Science and Technology Ministry at Kut city south of IRAQ at three
heights (10, 30, 50 m). The wind turbine selected for this study to be installed in the wind farm are Bonus-
300kw, 600kw The Annual Energy Production (AEP) has been calculate which varies between (746.990 -
759.446 MWH) at 30 m and it s varies between produced AEP (1.576 - 1.600 GWh) at 50 m ,this site classified
as ( class-1).
Presentation given by Dr Zia Wadud at the18th World Conference of the Air Transport Research Society, Bordeaux, France, July 2014.
atrs2014.org
www.its.leeds.ac.uk/people/z.wadud
Improvement of Pitch Motion Control of an Aircraft SystemsTELKOMNIKA JOURNAL
ย
The movement of the aircraft pitch is very important to ensure the passengers and crews are in
intrinsically safe and the aircraft achieves its maximum stability.The objective of this study is to provide a
solution to the control system that features particularly on the pitch angle motion of aircraft systemin order
to have a comfort boarding. Three controllers were developed in these projects which wereproportional
integral derivative (PID), fuzzy logic controller (FLC), and linear quadratic regulator (LQR) controllers.
These controllers will help improving the pitch angle and achievingthe target reference. By improving the
pitch motion angle, the flight will be stabilized and in steady cruise (no jerking effect), hence provides all
the passengers withthe comfort zone. Simulation results have been done and analyzed using Matlab
software. The simulation results demonstrated LQR and FLC were better than PID in the pitch motion
system due to the small error performance. In addition, withstrong external disturbances, a single controller
is unable to control the system, thus, the combination of PID and LQR managed to stabilize the aircraft.
Aerial Ambulance Stretcher Drone Design and Implementation Mohammad Zimmo
ย
This project is an aerial ambulance stretcher drone that aims to facilitate providing immediate medical care for severely injured babies in accidents. The current ambulance vehicle is incapable of providing the necessary health care in such situations, which is the main motivation of this project. After the project had been picked and the designed had been finalized, the project was built by first assembling the drone piece by piece. Then, additional systems are added to the drone to adapt it to perform its task. Examples of added subsystems are the obstacle avoidance and landing gears systems. Finally, the systems were tested and they turned out to be working properly
Some thoughts on how Unmanned Aerial Vehicles may change how some businesses maintain inventories as a prelude to required infrastructure to support UAV operations.
Discussion of required support Infrastructure for Unmanned Aerial Vehicles (UAV's,) in context of expanded use by Commercial, Personal & Government markets. (Episode 3 of 3)
Final presentation by University of Alabama in Huntsville at CanSat 2008
http://www.astronautical.org/2008/06/15/cansat-2008-university-of-alabama-in-huntsville/
Bioracermotion aero virtual wind tunnel. Bringing the wind tunnel to your living room. Learn and train your body to become faster with more sustainable power. Contact our team today and become faster tomorrow info@bioracermotion.com
The Centurion Orbit Transfer Vehicle (OTV) was part of our Aerospace Engineering Senior Design project at the University of Illinois at Urbana-Champaign. It is equipped with the latest technologies, including a nuclear thermal propulsion system. The structure weighs 89,000 kg and is capable of transporting cargo to Lagrange points L1 or L2.
Aerodynamics of flapping wing MAV
The question which I got from the panel was how to calculate the Reynolds number ?..the ans is by claculating MAC Mean Aerodynamic Chord
A Strategy for Reliability Evaluation and Fault Diagnosis of Autonomous Under...Koorosh Aslansefat
ย
Underwater vehicles contribute significantly to exploiting great maritime resources. Autonomous vehicles are one of the various kinds of underwater vehicles which are able to perform operations without operator's interference. Autonomous underwater vehicles can be classified according to their propulsion systems. Autonomous Underwater Gliders (AUG) are among autonomous underwater vehicles which fall under the category of glide type underwater vehicles. They are designed in a way that they benefit low energy consumption and a wide survey range. Their reliable design is one of the challenges facing their manufacturing. Fault tolerance is one of the important attributes in designing reliable systems. Recognizing, evaluating and facing the faults are of great importance in designing fault tolerant systems. This paper studies underwater Glider vehicles' subsystems, considers their faults and causes, and provides a typical fault tree for these vehicles form which glider reliability and the effects of glider subsystems on its failure can be driven.
The Mars Autogyro Neutroscopic Explorer defines a new design โX-Iโ which has been optimised to meet the challenge of the hostile Martian atmosphere. It blends in an autogyro rotor into a delta wing to enhance the lift capabilities of the aircraft in supersonic and sub sonic flight regimes. The diagrams below represent the chronological order in which the design was generated
Calculating Wind Farm Production in Al-Shihabi (South Of Iraq) Using WASPIJERA Editor
ย
The Wind Turbine farms are becoming popular in the renewable energy world. In this research, the Wind Atlas
Analysis and Application Program (WAsP) has been used to estimate wind power density in Al-Shihabi (south
of Iraq). All statistical operations on data series are obtained from Field data collected from the wind
measurement towers which installed by the Science and Technology Ministry at Kut city south of IRAQ at three
heights (10, 30, 50 m). The wind turbine selected for this study to be installed in the wind farm are Bonus-
300kw, 600kw The Annual Energy Production (AEP) has been calculate which varies between (746.990 -
759.446 MWH) at 30 m and it s varies between produced AEP (1.576 - 1.600 GWh) at 50 m ,this site classified
as ( class-1).
Presentation given by Dr Zia Wadud at the18th World Conference of the Air Transport Research Society, Bordeaux, France, July 2014.
atrs2014.org
www.its.leeds.ac.uk/people/z.wadud
Improvement of Pitch Motion Control of an Aircraft SystemsTELKOMNIKA JOURNAL
ย
The movement of the aircraft pitch is very important to ensure the passengers and crews are in
intrinsically safe and the aircraft achieves its maximum stability.The objective of this study is to provide a
solution to the control system that features particularly on the pitch angle motion of aircraft systemin order
to have a comfort boarding. Three controllers were developed in these projects which wereproportional
integral derivative (PID), fuzzy logic controller (FLC), and linear quadratic regulator (LQR) controllers.
These controllers will help improving the pitch angle and achievingthe target reference. By improving the
pitch motion angle, the flight will be stabilized and in steady cruise (no jerking effect), hence provides all
the passengers withthe comfort zone. Simulation results have been done and analyzed using Matlab
software. The simulation results demonstrated LQR and FLC were better than PID in the pitch motion
system due to the small error performance. In addition, withstrong external disturbances, a single controller
is unable to control the system, thus, the combination of PID and LQR managed to stabilize the aircraft.
Aerial Ambulance Stretcher Drone Design and Implementation Mohammad Zimmo
ย
This project is an aerial ambulance stretcher drone that aims to facilitate providing immediate medical care for severely injured babies in accidents. The current ambulance vehicle is incapable of providing the necessary health care in such situations, which is the main motivation of this project. After the project had been picked and the designed had been finalized, the project was built by first assembling the drone piece by piece. Then, additional systems are added to the drone to adapt it to perform its task. Examples of added subsystems are the obstacle avoidance and landing gears systems. Finally, the systems were tested and they turned out to be working properly
Some thoughts on how Unmanned Aerial Vehicles may change how some businesses maintain inventories as a prelude to required infrastructure to support UAV operations.
Discussion of required support Infrastructure for Unmanned Aerial Vehicles (UAV's,) in context of expanded use by Commercial, Personal & Government markets. (Episode 3 of 3)
Another compromised hostname โhttps://xxx.comโ is acting like drop-zone for stolen data from eight different Italian banks. The analysis of this drop-zone reveal a custom web application focused for info stealing. They steal a credit card details from the infected users using a phishing attack.
Modeling and control approach to a distinctive quadrotor helicopterISA Interchange
ย
The referenced quadrotor helicopter in this paper has a unique configuration. It is more complex than commonly used quadrotors because of its inaccurate parameters, unideal symmetrical structure and unknown nonlinear dynamics. A novel method was presented to handle its modeling and control problems in this paper, which adopts a MIMO RBF neural nets-based state-dependent ARX (RBF-ARX) model to represent its nonlinear dynamics, and then a MIMO RBF-ARX model-based global LQR controller is proposed to stabilize the quadrotor's attitude. By comparing with a physical model-based LQR controller and an ARX model-set-based gain scheduling LQR controller, superiority of the MIMO RBF-ARX model-based control approach was confirmed. This successful application verified the validity of the MIMO RBF-ARX modeling method to the quadrotor helicopter with complex nonlinearity.
Selection and evaluation of FOPID criteria for the X-15 adaptive flight cont...Hamzamohammed70
ย
Recently, there has been a growing interest among academics worldwide in studying flight control systems. The
advancement of tracking technologies, such as the X-15 adaptive flight control system developed at NASA
(National Aeronautics and Space Administration), has sparked significant exploration efforts by scientists. The
vast availability of aerial resources further contributes to the importance of studying adaptive flight control
systems (AFCS). The successful operation of AFCS relies on effectively managing the three fundamental motions:
pitch, roll, and yaw. Therefore, scientists have been diligently working on developing optimization algorithms
and models to assist AFCS in achieving optimal gains during motion. However, in real-world scenarios, each
motion requires its own set of criteria, which presents several challenges. Firstly, there are multiple criteria
available for selecting appropriate optimization values for each motion. Secondly, the relative importance of
these criteria influences the selection process. Thirdly, there is a trade-off between the performance of the criteria
within a single optimization case and across different cases. Lastly, determining the critical value of the criteria
poses another obstacle. Consequently, evaluating and selecting optimum methods for AFCS trajectory controls
becomes a complex operation. To address the need for optimizing AFCS for various maneuvers, this study
proposes a new selection process. The suggested approach involves utilizing black hole optimization (BHO), Jaya
optimization algorithm (JOA), and sunflower optimization (SFO) as methods for detecting and correcting trajectories in adaptive flight control systems. These methods aim to determine the best launch of missiles from the
AFCS based on the coordinate location for both long and short distances. Additionally, the methods determine
the optimal gains for the FOPID (fractional order proportional integral derivative) controller and enhance protection against enemy attacks. The research framework consists of two parts. The first part focuses on improving
the FOPID motion gains by employing optimization algorithms (BHO, JOA, and SFO) that are evaluated based on
the FOPID criteria. Lower significant weighting values of the optimization algorithms demonstrate the best
missile launching in a cosine wave trajectory within AFCS, while higher significant values indicate the best
missile launching in a sine wave trajectory within AFCS. The FOPID controller criteria, including Kp_pitch, Ki_roll,
Kd_yaw, ฮป_pitch, and ยต_yaw, are considered in all situations. Furthermore, the study reports the best weights
obtained for the "Kp_pitch" criterion across the motions as follows: (0.8147, 66.7190, and 54.4716). For the
"Ki_roll" criterion, the best weights are (0.0975, 64.4938, and 64.7311), and for "Kd_yaw" the weights are (0.1576,
35.2811, and 54.3886). The results of the selection process by the BHO, JOA, and SFO algorithms.
K. Alexis, C. Papachristos, G. Nikolakopoulos, A. Tzes, โModel Predictive Quadrotor Indoor Position Controlโ, 19th Mediterranean Conference on Control and Automation, p.1247-1252, June 20-23 2011, Aquis Corfu Holiday Palace, Corfu, Greece
Memorandum Of Association Constitution of Company.pptseri bangash
ย
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
www.seribangash.com
Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
ย
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
Buy Verified PayPal Account | Buy Google 5 Star Reviewsusawebmarket
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[Note: This is a partial preview. To download this presentation, visit:
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Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
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1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
ย
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
Accpac to QuickBooks Conversion Navigating the Transition with Online Account...PaulBryant58
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This article provides a comprehensive guide on how to
effectively manage the convert Accpac to QuickBooks , with a particular focus on utilizing online accounting services to streamline the process.
RMD24 | Debunking the non-endemic revenue myth Marvin Vacquier Droop | First ...BBPMedia1
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Marvin neemt je in deze presentatie mee in de voordelen van non-endemic advertising op retail media netwerken. Hij brengt ook de uitdagingen in beeld die de markt op dit moment heeft op het gebied van retail media voor niet-leveranciers.
Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
Skye Residences | Extended Stay Residences Near Toronto Airportmarketingjdass
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Putting the SPARK into Virtual Training.pptxCynthia Clay
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This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
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As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
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๐๐ ๐๐จ๐ฆ๐ฌ (๐๐ ๐๐จ๐ฆ๐ฆ๐ฎ๐ง๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
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"๐๐ฏ๐๐ซ๐ฒ ๐๐ฏ๐๐ง๐ญ ๐ข๐ฌ ๐ ๐ฌ๐ญ๐จ๐ซ๐ฒ, ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ฅ ๐ฃ๐จ๐ฎ๐ซ๐ง๐๐ฒ. ๐๐ ๐๐ฅ๐ฐ๐๐ฒ๐ฌ ๐๐๐ฅ๐ข๐๐ฏ๐ ๐ญ๐ก๐๐ญ ๐ฌ๐ก๐จ๐ซ๐ญ๐ฅ๐ฒ ๐ฒ๐จ๐ฎ ๐ฐ๐ข๐ฅ๐ฅ ๐๐ ๐ ๐ฉ๐๐ซ๐ญ ๐จ๐ ๐จ๐ฎ๐ซ ๐ฌ๐ญ๐จ๐ซ๐ข๐๐ฌ."
Improving profitability for small businessBen Wann
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In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
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1. Control of Cooperative
Unmanned Aerial Vehicles
Kostas Alexis
Department of Electrical
& Computer Engineering,
University of Patras, Greece
1
2. Structure of this presentation
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 2
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
3. History of UAVs
Some of the most wide-
spread UAV designs are
inspired from old manned
aircraft designs that did not
convince the market in their
times.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
3
๏ง Unmanned Aerial Vehicles can be tracked back
to the beginnings of 20th century operating in
military missions.
๏ง UAVs started as remote piloted vehicles but
due to technological and scientific
advancements autonomous systems became
feasible.
๏ง The end of 2oth century was a turning point in
the history of robotics: production expanded
massively to domestic use.
๏ง Currently UAV designs for civilian applications
mainly focus in miniaturizing existing fixed-
wing and rotorcraft designs.
4. Scientific Motivation
Unmanned Aerial Vehicles and specially quadrotor rotorcrafts pose significant
scientific and engineering challenges:
๏ง Very aggressive nonlinear, underactuated dynamics.
๏ง They are affected from complex aerodynamic phenomena.
๏ง Prone to perturbations due to atmospheric turbulence.
๏ง Low-cost miniaturized sensor estimation systems are noisy, they drift and are
very prone to vibrations.
๏ง Hard actuation constraints in terms of dynamic range, precision, response
time, nonlinear characteristics and relatively high power consumption.
๏ง Despite their small size they are still complex machines that need increased
computational power.
Design and autonomous control of such systems is still an open challenge!
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
4
5. Socioeconomic Motivation
Unmanned Aerial Vehicles (and specially quadrotors)
can be utilized in a wide set of real-life applications:
๏ง Intelligence, Surveillance, Reconnaissance (ISR)
๏ง Wild-fire surveillance
๏ง Agricultural services
๏ง Search & Rescue
๏ง Buildings inspection
๏ง Area Exploration & Mapping
๏ง Military applications
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
5
6. State of the Art
Research groups around the world
have achieved very promising results
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
6
7. Contributions of this work [1/2]
The Contributions of this work reside in the following areas:
1. Modeling of the quadrotor dynamics using Piecewise Affine systems: until
now linear and nonlinear models of the quadrotor dynamics have been proposed.
Piecewise Affine systems-based modeling provides the opportunity to:
a. capture some of the nonlinearities and couplings of the system - cover a
relatively large part of the systemโs flight envelope.
b. utilize linear control theory.
2. UPATcopter Design: The UPATcopter is an efficient and modular quadrotror
experimental platform emphasizing in the areas of:
a. powerful onboard computational capabilities
b. autonomous indoor state estimation based on inertial measurements, sonar data and
vision sensors
c. extended communication options
d. low-cost but efficient actuators.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
7
8. Contributions of this work [2/2]
3. System Control: Three different Control strategies were designed and
experimentally verified for their performance:
a. A Switching Model Predictive Controller for the 6-Degrees of Freedom trajectory control
of the quadrotor.
b. A Constrained Finite Time Optimal Controller for the quadrotorโs attitude control
problem.
c. A Proportional-Integral-Derivative-2ndDerivative /Proportional-Integral-Derivative
controller for the quadrotorโs rotational/translational motion dynamics. This control
augments classical PID controllers with angular acceleration feedback.
4. UAV cooperation: two cooperation strategies have been proposed in order to
address the problems of a) cooperative forest fire surveillance and b) area
exploration
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
1. Introduction
8
9. Quadrotor Modeling Approach
9
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
10. Modeling Assumptions
Quadrotorโs Forward Motion: difference in the lift
produced from the front and rear rotors
Quadrotorโs Sideward Motion: difference in the lift
produced from left and right rotors
Quadrotorโs Yaw motion: difference in the
counter-torque between the counter-rotating
rotor pairs
Perpendicular motion: rotorsโ overall thrust
Dynamics modeling assumptions:
1. Rigid and symmetrical structure.
2. CoG and Body Fixed Frame coincide.
3. Rigid propellers.
4. Thrust and drag forces proportional to the
square of propellerโs speed.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
2. Quadrotor Modeling Approach
10
11. Forces & Moments acting on the craft [1/2]
Newton-Euler Formulation
F: force vector on the CoM
ฯ: total torque acting about the CoM
I3x3: indentity matrix
I: Inertia moment about the CoM
m: total mass of the body
V: acceleration of the CoM
ฯ: angular velocity
CoM: Center of Mass
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 11
2. Quadrotor Modeling Approach
Rotation Matrix from BFF to EFF:
Transformation of craft rates
expressed in BFF and EFF:
12. Forces & Moments acting on the craft [2/2]
Main aerodynamic forces and moments:
1. Thrust force: the resultant of the vertical forces acting on all blade elements
2. Hub force: the resultant of the horizontal forces acting on all blade elements
3. Drag moment: the moment about the rotor shaft due to aerodynamic forces
4. Rolling moment: the moment produced in forward flight when the advancing blade is
producing more lift than the retreating one
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 12
2. Quadrotor Modeling Approach
Ground Effect: when a rotorcraft is operating very close to ground (half of a
rotorโs diameter) experiences thrust augmentation due to the interference
of the surface with the airflow pattern of the rotor system.
13. Piecewise Affine Modeling Approach [1/3]
Euler-Lagrange formulation 6DOF Quadrotor Dynamics Modeling
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 13
2. Quadrotor Modeling Approach
The angles ฯ,ฮธ,ฯ are independent of the translational motion
Altitude motion dynamics can be decoupled from horizontal
motion dynamics
14. Piecewise Affine Modeling Approach [2/3]
Attitude Piecewise Affine representations
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 14
2. Quadrotor Modeling Approach
Discrete Time Expression
Piecewise
modeling
Augmented with Integral Terms
Disturbance effects in
attitude rates.
15. Piecewise Affine Modeling Approach [3/3]
Vertical Piecewise Affine Error Dynamics Translational Piecewise Affine Error Dynamics
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 15
2. Quadrotor Modeling Approach
Augmented with Integral Terms
Augmented with Integral Terms
Piecewise
modeling
16. Aerodynamic Effects
In classical quadrotor modeling the aerodynamic effects due to variation of the
airstream are neglected. However, even at moderate translational velocities or
for moderate wind-gusts, their impact becomes important.
1. Blade Flapping
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 16
2. Quadrotor Modeling Approach
2. Total Thrust variation
3. Airflow Disruption
17. Simulink Model
Based on experimental measurements and CAD/CAM computation a MATLAB-
Simulink model was derived in order to aid the control design process.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 17
2. Quadrotor Modeling Approach
18. Quadrotor Modeling Conclusions
New method for the modeling of the quadrotorโs dynamics has been proposed
based on the theory of Piecewise Affine Systems.
Advantages:
๏ง Captures nonlinearities and couplings of the system โ Covers a larger part of
the quadrotorโs flight envelope compared to linear approaches.
๏ง Takes into account the disturbance effects of atmospheric turbulence as
affine-additive terms.
๏ง Provides the opportunity to utilize Optimal/Switching control theory.
๏ง Can be expanded to other rotorcrafts types.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 18
2. Quadrotor Modeling Approach
19. Quadrotor Design
19
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
20. System Requirements
The design of the UPATcopter quadrotor experimental platform should fit the
following requirements:
๏ง The craft should be of small-size with about 0.5m diameter.
๏ง The craft should not exceed 1.5Kg while also providing more than 0.5Kg
additive payload.
๏ง The craft should have high-end processing capabilities.
๏ง The craft should be able of complete autonomous indoor and outdoor state
estimation.
๏ง The craft should have multiple wireless communication options.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
3. Quadrotor Design
20
21. Experimental Platforms
In the beginning of this research a Draganflyer VTi helicopter was utilized but it
was soon proved that could not fit the aforementioned requirements.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
3. Quadrotor Design
21
Draganflyer Vti Toy Quadrotor
First attempt of quadrotor design
22. Experimental Platforms
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras
3. Quadrotor Design
22
Second UPATcopter platform
Final UPATcopter design
Carbon fiber centerplates
Anodized aluminum arms
Nylon/Carbon fiber propellers
s
23. UPATcopter main hardware diagram
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 23
3. Quadrotor Design
24. Main Control Unit
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 24
3. Quadrotor Design
All โ in โ one Single Board Computers can be utilized as Powerful, low-power, low-weight and low-
cost Main Control Units.
This approach provides the capability to rapidly develop and deploy control, cooperation and
environmental perception algorithms using high-level programming methods and high-end
operation systems.
picoITX was selected as the Main Control Unit of UPATcopters โข 1.6GHz ATOM Z530 Processor
able to cope with all required
control and perception
computations
โข 2GB RAM
โข Modular connectivity through
USB Ports, I2C Bus, SPI โ All
sensors can be easily used
โข Easily combined with Wireless
Networks adapters
โข Less than 0.5A at 5V
โข Less than 250g with Memory and
SSD Hard Disk Drive
25. Sensor System โ Attitude/Altitude Estimation
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 25
3. Quadrotor Design
Xsens MTi-G Attitude
Heading Reference System
Open-Source IMUs
12oHz Maximum update rate
Relatively low drifting
Closed firmware
100Hz Maximum update rate
Drifting
Very prone to vibrations
30o degrees beam sonar
provides altitude data
26. Sensor System โ Indoor horizontal motion estimation
One of the most demanding problems of complete indoor state estimation is
that of horizontal motion measurement and estimation. This problem can be
solved either by using fixed cameras (higher accuracy, very high cost, not
autonomous solution) or by designing onboard position estimation systems.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 26
3. Quadrotor Design
2 Optic Flow Systems were Developed
Mouse Sensor Based Optic Flow Tam 2Micro Vision chip solution
The Tam2 vision chip based optic flow solution implements the Image Interpolation
Algorithm (I2A) in order to derive optic flow measurements from the pixel array.
I2A algorithm computes the amplitude of the translation sd between an image
region I(n,t) captured at time t, and a later image I(n,t+ฮt)
27. Propulsion Group
๏ง Accurate control of motor-propeller control is critical in order to achieve increased
flight accuracy.
๏ง DC โ brushless motors were utilized due to their increased torque characteristics.
๏ง The appropriate programming of the Electronic Speed Controller in high update rates
(>100Hz/I2C Bus), the power consumption and the identification of the final Speed
Controller-Motor-Propeller system is important for the overall control problem.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 27
3. Quadrotor Design
28. Quadrotor Control Approaches
28
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
29. Proposed Control Strategies
๏ง A Constrained Finite Time Optimal Control (CFTOC) Strategy for the Quadrotorโs
attitude set-point problem.
๏ง A Switching Model Predictive Control (SMPC) Strategy for the Quadrotorโs
trajectory/attitude control problem.
๏ง A Proportional-Integral-Derivative-2nd Derivative/ Proportional-Integral-Derivative
Control Strategy for the Quadrotorโs Attitude/Translational dynamics.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 29
4. Quadrotor Control Approaches
30. Constrained Finite Time Attitude Optimal Control
System Piecewise Affine Dynamics:
Goals:
Capture nonlinearities of the attitude subsystem
Account for state and input constraints of the system
Account for the additive effects of wind-gust disturbances
Explicit Solution โ Offline Computation
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 30
4. Quadrotor Control Approaches
31. Constrained Finite Time Attitude Optimal Control
Input Constraints:
State Constraints
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 31
4. Quadrotor Control Approaches
32. Constrained Finite Time Attitude Optimal Control
Assuming Ts sampling period
Compute the optimal control sequence:
Cost function subject to PWA dynamics:
The control action is a continuous function of the following form:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 32
4. Quadrotor Control Approaches
Convex Polyhedron
Number of created polyhedra
33. Constrained Finite Time Attitude Optimal Control
Experimental studies with an initial experimental set-up consisted of a Draganflyer VTi
quadrotor, Xsens MTi-G IMU and personal computer.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 33
4. Quadrotor Control Approaches
Tait-Bryan angle rates are
not equal with p,q,r rates
s
34. Constrained Finite Time Attitude Optimal Control
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 34
4. Quadrotor Control Approaches
35. Constrained Finite Time Attitude Optimal Control
Attitude Regulation for 1-3-5 PWA systems
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 35
4. Quadrotor Control Approaches
36. Constrained Finite Time Attitude Optimal Control
Attitude Regulation for 1-3-5 PWA systems subject to forcible Wind-Gusts
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 36
4. Quadrotor Control Approaches
37. Constrained Finite Time Attitude Optimal Control
Comparison of LQ (red) โ CFTOC (blue)
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 37
4. Quadrotor Control Approaches
38. Constrained Finite Time Attitude Optimal Control
Response subject to different directional wind-gusts
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 38
4. Quadrotor Control Approaches
39. Constrained Finite Time Attitude Optimal Control
In conclusion:
1. CFTOC can be computed over a family of Piecewise Affine systems.
2. Ensures stability among the switching.
3. Accounts for the state and input constraints of the system.
4. Efficient in wind-gust disturbances attenuation.
5. Multi-Parametric solution has the advantage of off-line computation.
6. However: excessive computational cost for systems with more than 4 states
and prediction horizon larger than 5 steps aheadโ inefficient onboard
implementation. This is due to the exponential number of transitions
between regions which can occur when a controller is computed in a
dynamic programming fashion.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 39
4. Quadrotor Control Approaches
40. Switching Model Predictive Control
Why Model Predictive Control:
1. It handles multivariable control problems naturally.
2. It can take into account actuator and state limitations.
3. It allows operation close to constraints โ more profitable operation.
4. Receding horizon โideaโ can lead to smoother response
Why not:
1. Increased computational costs.
2. Requires good knowledge of the model.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 40
4. Quadrotor Control Approaches
Kontron pITX &
good programming ==
Problem Solved!
Can be solved with
extended simulations,
CAD tools and
experimental studies.
Main contributions of the proposed SMPC strategy:
1. First time to design and experimentally verify a Model Predictive Control for
the quadrotorโs attitude and trajectory control problem.
2. Switching control based on multiple Piecewise Affine system
representations.
3. Accounts for the additive effects of wind-gusts due to affine terms in the
model.
4. Accounts for the state and input constraints of the quadrotor.
5. Experimentally verified based on Inertial sensors, Sonar and Optic Flow
position deviation measurements. The proposed system achieves accurate
position control both in the absence and under the presence of wind-gusts,
trajectory tracking and accurate attitude maneuvering.
Submitted at IET Control Theory and
Applications
41. Switching Model Predictive Control
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 41
4. Quadrotor Control Approaches
42. Switching Model Predictive Control
Discretized Attitude, Altitude and Horizontal Piecewise Affine Dynamics:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 42
4. Quadrotor Control Approaches
43. Switching Model Predictive Control
State and Input Constraints:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 43
4. Quadrotor Control Approaches
Attitude Constraints Vertical Constraints Horizontal Constraints
44. Switching Model Predictive Control
For each Piecewise Affine system:
with respect to the control moves and the Piecewise Affine
system dynamics, where:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 44
4. Quadrotor Control Approaches
Prediction horizon (=5)
Control horizon (=2)
45. Switching Model Predictive Control
Selected Piecewise Operation Regions and Linearization Points (ฮ>>1):
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 45
4. Quadrotor Control Approaches
46. Switching Model Predictive Control
Position Hold:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 46
4. Quadrotor Control Approaches
47. Switching Model Predictive Control
Position Hold under Wind-Gusts:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 47
4. Quadrotor Control Approaches
48. Switching Model Predictive Control
Trajectory Control:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 48
4. Quadrotor Control Approaches
49. Switching Model Predictive Control
Hover subject in the absence and under the presence of wind-gusts
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 49
4. Quadrotor Control Approaches
50. Switching Model Predictive Control
Attitude Maneuver
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 50
4. Quadrotor Control Approaches
51. Switching Model Predictive Control
In conclusion:
1. Model Predictive Control is very promising for such complex multivariable
systems.
2. It poses significant advantages including its abilities to account for the
physical constraints of the system and the effects of atmospheric
disturbances.
3. Switching control counts for some of the nonlinearities of the system and
produces control actions for a large part of the quadrotorโs flight envelope.
4. The drawback of increased computational costs can be resolved.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 51
4. Quadrotor Control Approaches
52. PIDD/PID Attitude/Position Control
Proportional โ Integral โ Derivative โ 2nd Derivative Attitude Control
1. Based on classical PID theory augmented with angular acceleration
feedback.
2. Extends the bandwidth of the closed-loop system โ provides the opportunity
to increase the control gains.
3. Leads to faster tracking response.
Translational dynamics are relatively slow โ classical PID was utilized
This control law was designed in order to use the computational power of the
Kontron pITX for other computations (Environmental Perception)
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 52
4. Quadrotor Control Approaches
55. PIDD/PID Attitude/Position Control
Position Hold:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 55
4. Quadrotor Control Approaches
56. PIDD/PID Attitude/Position Control
Attitude Regulation
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 56
4. Quadrotor Control Approaches
57. PIDD/PID Attitude/Position Control
Aggressive Attitude Regulation
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 57
4. Quadrotor Control Approaches
58. PIDD/PID Attitude/Position Control
PIDD/PID control:
1. Combination of classical PID control schemes and angular acceleration
feedback.
2. Efficient & Simple โ low computational cost.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 58
4. Quadrotor Control Approaches
59. Cooperation of Unmanned
Aerial Vehicles
59
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
60. Cooperating UAVs
UAVs are utilized in more complex missions and specially ISR (Intelligence, Surveillance
and Reconnaisance). Such missions pose a number of challenging requirements:
1. Environmental Perception
2. Navigation under Uncertainty
3. Mission Critical Issues (i.e. timing)
4. Redundancy
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 60
5. Cooperation of UAVs
Cooperative UAVs
61. Cooperative Forest-Fire Surveillance
๏ง This mission is solved using an overlapping cooperation approach.
๏ง The overlapping strategy is based on simple Consensus implemented in each
UAV, while the communication between the UAVs is carried according to the
consensus algorithm:
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 61
5. Cooperation of UAVs
62. Cooperative Forest-Fire Surveillance
Forest Fire propagation model required for simulation studies:
๏ง Although there are complex models based on statistic data, simple geometrical
models that assume that the fire perimeter expands like an ellipse or a folium in
relation with the windโs blowing direction are adequate for UAV cooperation
simulation studies.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 62
5. Cooperation of UAVs
63. Cooperative Forest-Fire Surveillance
Operation goal: track every point of the evolving fire perimeter and update the location
of the fire with the least latency.
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 63
5. Cooperation of UAVs
Objective: Equalize the paths flown by the quadrotors
65. Simulation Test Case:
1. The fire perimeter is an ellipse and the evolution is modeled as a change on the ellipse
foci affecting its major and minor radius. The change in perimeter occurs in T=1hr,2hrs
and 4hs respectively.
2. Each quadrotor communicates only with the quadrotor with which they meet in a
rendezvous point.
3. Quadrotors that have met in a rendezvous point sense fire perimeter changes. If a
variation of the perimeter is sensed then both quadrotors fly to the new fire
perimeter at its closed point.
Cooperative Forest-Fire Surveillance
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 65
5. Cooperation of UAVs
66. Heterogeneous UAV Swarm Area Exploration and Target
Acquisition
Heterogeneous UAV Swarm โ Cooperation strategies should account for the different
vehicle capabilities, advantages and drawbacks.
Assume a UAV Swarm consisted of Quadrotors with different characteristics
Quadrotors can fly forward but also hover above a target for constant surveillance: the
cooperation strategy must also benefit from this capability
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 66
5. Cooperation of UAVs
The goal of the UAV-Swarm is to enter an
unknown fixed dimensions area with
static targets, explore as soon as
possible, acquire the target positions and
constantly survey them.
67. Heterogeneous UAV Swarm Area Exploration and Target
Acquisition
Cooperation Strategy assumptions:
1. The fixed dimensions unexplored area is tessellated into equal sized square Cells, Cell(k,m).
2. Each UAV is equipped with two vision systems for forward look and downwards area
exploration.
3. Vi is the velocity factor of the i-th UAV
4. Ci is the camera factor expressing the exploration camera
capabilities of the i-th UAV
1. Ei is the remaining flight endurance of the i-th UAV
2. Ti is the number indicating the total allocated tasks from the i-th UAV
3. Li is the number indicating the accomplish tasks from the i-th UAV
4. Ai is the uncompleted allocated tasks to the i-th UAV
5. Ri is the number of the maximum tasks to be executed in one round
6. Mi is a binary value indicating if the i-th UAV is in hovering mode
7. Xi is a binary value indicating if the i-th UAV is available for exploration (it is not when it has
acquired a target)
8. fi is the front camera omnidirectional range of the i-th UAV
9. cvi are the cells viewed from the exploration camera of the i-th UAV at each time
10. dik,m is the distance between the i-th UAV and the center of Cell(k,m)
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 67
5. Cooperation of UAVs
68. Heterogeneous UAV Swarm Area Exploration and Target
Acquisition
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 68
5. Cooperation of UAVs
69. Heterogeneous UAV Swarm Area Exploration and Target
Acquisition
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 69
5. Cooperation of UAVs
70. Conclusions & Future Work
70
1. Introduction
2. Quadrotor Modeling Approach
3. Quadrotor Design
4. Quadrotor Control Approaches
5. Cooperation of UAVs
6. Conclusions and Future Work
71. Conclusions & Future Work
The main contributions of this Thesis are:
๏ง New Quadrotor dynamics modeling based on Piecewise Affine Systems theory
๏ง Design of a powerful and modular quadrotor experimental platform capable of very complex
computations, complete autonomous indoor state estimation and extended communication
capabilities.
๏ง Design and Experimental verification of Constrained Finite Time Optimal Controllers, Switching
Model Predictive Control strategies and PIDD/PID control schemes.
๏ง Two new UAV cooperation strategies were proposed in order to address the problems of forest
fire surveillance and area exploration.
Future Work:
1. Design of Miniature/Micro Aerial Vehicles based on novel flying concepts: a) convertible fixed-
wing to rotorcraft or inspired by nature, and b) transformerable UGV-UAV, AUV-UAV
2. Design of control laws and environmental perception that would ensure precise navigation
under severe environmental disturbances by studying the nature of the aerodynamic effects
3. Design and experimental verification of fully decentralized cooperation strategies for large
heterogeneous UAV swarms
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 71
6. Conclusions & Future Work
72. Conclusions & Future Work
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 72
6. Conclusions & Future Work
UAV WSN
Micro-Quadrotor
Environmental
Perception
Convertible UAV: Tilt-Rotor
KA-GN
CP-KA
Samara Blade
73. Thank you for your
attention!
Thank you for your
attention!
Control of Cooperative Unmanned Aerial Vehicles โ Kostas Alexis, University of Patras 73
Control of Cooperative Unmanned Aerial Vehicles