SUBJECT: Ph.D. Dissertation Defense
BY: Martin Cacan
TIME: Thursday, November 3, 2016, 2:30 p.m.
PLACE: Student Center, 319
TITLE: Adaptive Control of Autonomous Airdrop Systems in Degraded Conditions
COMMITTEE: Dr. Mark Costello, Chair (AE/ME)
Dr. Aldo Ferri (ME)
Dr. William Singhose (ME)
Dr. Eric Johnson (AE)
Gregory Noetscher (US Army)


Autonomous airdrop systems exhibit significant improvements over their unguided counterparts due to the addition of control mechanisms and real-time feedback. Increased landing accuracy comes with a high dependence on accurate sensor measurements (primarily GPS) and a consistent nominal system and environment. Unfortunately, airdrop systems represent a highly uncertain class of aerial vehicles where operation at off-nominal, degraded conditions is the norm and not the exception. Degraded conditions are caused by numerous effects including: parafoil rigging changes caused by canopy opening shock, parafoil damage during canopy inflation, parafoil canopy collapse, payload mass and inertial loading imbalances, human rigging errors, etc. Additionally, the loss of GPS feedback due to environmental causes (urban or canyon environments blocking the signal or causing multi-pathing issues) and active GPS denial by tech savvy adversaries present a second classification of degraded flight. These issues must be addressed to aid the continued expansion of the parafoil technology for delivery and re-entry purposes. This work applies two solutions to overcome the problems of physical degraded flight conditions and loss of GPS feedback. A highly adaptive control law is embedded at the core of the new guidance, navigation and control (GNC) algorithm to identify system dynamics and control sensitivity through the use of a discrete nonlinear Hammerstein dynamic model. All model parameters are estimated in-flight to maintain a high level of landing accuracy under a large range of degraded flight conditions. In addition, an analysis into the feasibility of radio frequency (RF) beacons as a redundant feedback system to GPS is analyzed. Novel GNC algorithms are introduced to handle the limited feedback that RF beacons provide in comparison to the rich data embedded in GPS. Performance of the proposed autonomous algorithms are tested through rigorous simulation of a validated flight dynamic model and experimental testing on a small scale autonomous parafoil and payload system.