Team #9 Julian Jaramillo Craig Cobabe Edward Robinson Chris Pitts Oct 15, 2012 Create a fuzzy logic...
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STATUS REPORT #5 UAV - ADAPTABLE FUZZY LOGIC CONTROLLER Team #9 Julian Jaramillo Craig Cobabe Edward Robinson Chris Pitts Oct 15, 2012 Create a fuzzy logic controller that utilizes a neural network to control a wide range of aerial vehicles.
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Transcript of Team #9 Julian Jaramillo Craig Cobabe Edward Robinson Chris Pitts Oct 15, 2012 Create a fuzzy logic...
STATUS REPORT #5UAV - ADAPTABLE FUZZY
LOGIC CONTROLLER
Team #9
Julian Jaramillo
Craig Cobabe
Edward Robinson
Chris Pitts
Oct 15, 2012
Create a fuzzy logic controller that utilizes a neural network to control a
wide range of aerial vehicles.
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
Neural Network integration – 10/26/12
Simulation and real flight testing – 11/12/12
TASKS COMPLETED Tuned PI gains for attitude controllers
Verified simulator model will workException – yaw control
Website
ONGOING/PENDING TASKSOngoing Beginning testing fuzzy controller in
simulator. Make a more user friendly gui Repair helicopter
Pending Real flight testing with fuzzy controllers
UPCOMING TASKS Begin first draft of final report
10%
15%
15%BLOCK DIAGRAM
95%
50%
CURRENT SCHEDULE
