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Status Report #6 UAV - Adaptable Fuzzy logic controller

This report outlines the progress made in creating a fuzzy logic controller powered by a neural network for UAVs, showcasing their advantages over manned systems. The project aims to simplify the integration of UAVs with effective attitude feedback controllers. Key milestones include development of a fuzzy library, enhancements to the GUI, and both simulation and flight testing. Ongoing tasks involve fine-tuning the fuzzy controller and preparing for real-flight assessments. Future steps include preparing a final report and finalizing the prototype for demonstration.

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Status Report #6 UAV - Adaptable Fuzzy logic controller

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  1. Status Report #6UAV - Adaptable Fuzzylogic controller Oct 22, 2012 Team #9 Julian Jaramillo Craig Cobabe Edward Robinson Chris Pitts • Create a fuzzy logic controller that utilizes a neural network to control a wide range of aerial vehicles.

  2. Overall Need • UAV’s are better than manned systems for many tasks. However, UAV’s are hard to integrate because creating attitude feedback controllers is difficult. Milestones • Fuzzy library code – 9/28/12 • Version 2 of GUI – 10/29/12 • Simulation and real flight testing – 11/12/12

  3. Tasks Completed • Verified simulator model will work • Exception – yaw control • Website • Helicopter Rebuilt • Fuzzy Controller for Pitch

  4. Ongoing/Pending Tasks Ongoing • Testfuzzy controller for in simulator. • Real flight testing with fuzzy controllers ( Roll, Yaw) • Make a more user friendly GUI Pending • Demo day poster

  5. Upcoming Tasks • First draft of final report • Begin tuning Raptor 90

  6. BLOCK dIAGRAM 15% 15% 10%

  7. Current Schedule

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