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Multi-Agent Control Using Fuzzy Logic

Cook, Brandon M
http://orcid.org/0000-0002-9819-5234
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447688633

Abstract Details

2015, MS, University of Cincinnati, Engineering and Applied Science: Aerospace Engineering.
In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of Unmanned Aerial Systems (UAS) continue to multiply. Therefore, solutions to managing vehicles in highly congested airspace must be explored. In this study, an intelligent systems approach was used to help mitigate the risk of collision between aircraft in uncontrolled airspace using a UAS Traffic Management (UTM) System. To test the effectiveness of this system, a three-dimensional environment was created using MATLAB to simulate a fully autonomous heterogeneous fleet of UAS attempting to accomplish a variety of realistic missions, including precision agriculture, package delivery services, natural resource monitoring, and disaster management. Main research challenges include situational awareness, decision making, and multi-agent control in an uncertain, time-critical, spatio-temporal environment. To gain the knowledge, experience, and expertise necessary to solve this large-scale real-world problem, two preliminary research efforts were conducted. First, a simulated gaming platform known as Pong, originally created by ATARI, was used to demonstrate the effectiveness of a fully autonomous team to accomplish a desired task using a cascading Fuzzy system. With this knowledge, a simplified UTM system was developed to test a preliminary design of a fuzzy collision avoidance system. Once complete, this knowledge was used to develop the final UTM system platform capable of using intelligent separation assurance and collision avoidance techniques to mitigate the risk for Near Mid-Air Collisions between aircraft. This fuzzy solution utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The collision avoidance system was tested in extreme conditions, including close proximity, high closure rates, and conservative maximum turn rates. In the preliminary homogenous case, the collision avoidance techniques were on average 99.977% successful over a span of nearly 2,485 flight hours. Whereas, in the final UTM platform consisting of heterogeneous agents, the collision avoidance system was on average 99.88% successful over a span of 16,255 flight hours. Lastly, it was found that the techniques employed for separation assurance drastically mitigated the risk for Near Mid-Air Collisions. Comparing the unmitigated and mitigated cases, the number of losses of separation between aircraft reduced from one loss of separation per two flight hours, to one loss of separation per ten flight hours. This mitigated separation assurance platform was successful at preventing a loss of separation 88.47% of the time, over a span of 7,545 flight hours.
Kelly Cohen, Ph.D. (Committee Chair)
Manish Kumar, Ph.D. (Committee Member)
Grant Schaffner, Ph.D. (Committee Member)
Gary Slater, Ph.D. (Committee Member)
187 p.
Aerospace Materials
Fuzzy Logic; UAS Traffic Management; Unmanned Aerial Systems; Intelligent Systems; UAV Collision Avoidnace; Multi-Agent Control

Recommended Citations

Citations

  • Cook, B. M. (2015). Multi-Agent Control Using Fuzzy Logic [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447688633

    APA Style (7th edition)

  • Cook, Brandon. Multi-Agent Control Using Fuzzy Logic. 2015. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447688633.

    MLA Style (8th edition)

  • Cook, Brandon. "Multi-Agent Control Using Fuzzy Logic." Master's thesis, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447688633

    Chicago Manual of Style (17th edition)

ucin1447688633
678
© 2015, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.