TRAJECTORY OPTIMIZATION OF METEOROLOGICAL SAMPLING By KAEVON ALEXANDER AZARTASH-NAMIN Bachelor of Science in Mechanical & Aerospace Engineering Oklahoma State University Stillwater, Oklahoma 2016 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE July 2019 TRAJECTORY OPTIMIZATION OF METEORLOGICAL SAMPLING Thesis Approved: DR. JAMEY JACOB Thesis adviser DR. HE BAI DR. CHRISTOPHER CRICK ii Name: Kaevon Alexander Azartash-Namin Date of Degree: JULY 2019 Title of Study TRAJECTORY OPTIMIZATION OF METEORLOGICAL SAMPLING Major Field: MECHANICAL & AEROSPACE ENGINEERING ABSTRACT: Swarming involves controlling multiple unmanned aerial systems or UAS in formation through the use of controls and algorithms. Swarm systems may be distributed and not rely on a central controller. As a result, this gives the system the potential to be robust and scalable, allowing for flexibility for the engineers to approach problems differently. Based on a variety of a few models and algorithms, such as artificial potential fields (APFs), agent-based modeling, dynamic data driven application systems (DDDAS), and virtual structures, it may be determined that using a variation of one of these would be the best course of action for formation flight for a swarm of UASs. Choosing the right controller is dependent on what works best for acquiring atmospheric data in a coordinated formation. Current atmospheric data is commonly taken using a weather tower or mesonet. A mesonet is typically a 10m high tower with a pressure, temperature, humidity sensor placed at the top. Deciding which controller can be used to not only take useful atmospheric data, but in many cases replace a mesonet due to mobility and customization is the goal. A wind profile is a transient matter, so using a swarm vs using one drone or a mesonet helps to solve the issues that the latter two run into due to time and space. A swarm can record multiple points at one time due to each agent being a data point representation, whereas a single drone can only account for a single location in time. A swarm using a virtual structure (VS) can cover a variety of amounts of space in a coordinated shape. A meosnet is stationary and only oriented vertically and an uncoordinated group of UAS does not have the capability to operate together. This leaves the capability that a VS swarm has to fill in the gaps or even replace the traditional approaches. An array of sensor packages with mobility, coordinated movement, and endless data points could give the VS swarm the advantage in atmospheric data sampling. iii ACKNOWLEDGEMENTS I would like to acknowledge all of my research colleagues, peers, and professors for the support, advice and guidance throughout my undergraduate and graduate studies at Oklahoma State University. A personal acknowledgment to Dr. Jamey Jacob for his mentorship and guidance throughout the entirety of my education and this thesis research. I respect and look up to you more than you’ll know. A big thank you to Rakshit Dayal for your help, guidance, and friendship. This project flourished due to your mentorship and I can truly call you a brother. I have to give a big “Thank You” to my sister, fellow engineer, and friend. Though you’re in Aerospace because of me, thank you for being older so I can learn from your experiences. Thank you to my best friend and twin Bianca for your wisdom in not seeing the glass half full or empty, but where it really is. I want to acknowledge my parents, Nancy and Hossein, for them instilling a drive to be ambitious, take education serious, and reach for the stars. Lastly, I would like to thank the efforts on part of CLOUD-MAP and the National Science Foundation for their part in bringing together this research and funding in furthering the sciences associated with this project. Acknowledgements reflect the views of the author and are not endorsed by committee members or Oklahoma State University iv TABLE OF CONTENTS Chapter Page CHAPTER I .................................................................................................................................................. 1 1.INTRODUCTION ..................................................................................................................................... 1 1.1 Motivation ..................................................................................................................................... 1 1.2 Goals & Objectives ....................................................................................................................... 3 1.3 Outline of Thesis ........................................................................................................................... 3 CHAPTER II ................................................................................................................................................. 5 2.REVIEW OF LITERATURE .................................................................................................................... 5 2.1 Background ................................................................................................................................... 5 2.2 Artificial Potential Field................................................................................................................ 6 2.3 Agent-Based Modeling ................................................................................................................. 6 2.4 Dynamic Data Driven Application Systems (DDDAS) ................................................................ 7 2.5 Boundary Layer Meteorology ....................................................................................................... 7 2.6 Small UAS Atmospheric Boundary Layer Profiling .................................................................... 8 CHAPTER III ............................................................................................................................................. 11 3.THEORY ................................................................................................................................................. 11 3.1 Control Theory ............................................................................................................................ 11 3.1.1 Autonomous Controls ......................................................................................................... 11 A. Behavior Based Control .................................................................................................................. 11 B. Swarm UAS Model ......................................................................................................................... 12 3.1.2 Governing Equations........................................................................................................... 15 UAS Guidance and Control .................................................................................................................... 15 Virtual Structure...................................................................................................................................... 19 Graph Theory .......................................................................................................................................... 21 3.2 Application .................................................................................................................................. 21 3.2.1 Atmospheric Boundary Layer Profile ................................................................................. 21 v Chapter Page CHAPTER IV ............................................................................................................................................. 23 4.METHODOLOGY & EXPERIMENTAL ARRANGEMENT ............................................................... 23 4.1 Controller Design ........................................................................................................................ 23 4.1.1 Controller Design Considerations ....................................................................................... 23 4.1.2 Controller Design ................................................................................................................ 24 4.2 Simulation ................................................................................................................................... 25 4.4 Flight Testing .............................................................................................................................. 28 4.4.1 Sensors and System Layout ................................................................................................ 30 CHAPTER V .............................................................................................................................................. 38 5.RESULTS ................................................................................................................................................ 38 5.1 Swarm Results ............................................................................................................................ 38 5.2 Atmospheric Boundary Layer Profile Results ............................................................................ 56 CHAPTER VI ............................................................................................................................................. 58 6.CONCLUSIONS.....................................................................................................................................