Title

System Identification of a Small Low-Cost Unmanned Aerial Vehicle

Document Type

Presentation

Publication Date

4-10-2014

Faculty Mentor

Reese Fullmer

Abstract

Small low-cost unmanned aerial vehicles (UAVs) are a newly emerging resource for personal remote sensing for scientific research and civilian application. There are several obstacles that must be overcome before UAVs can be successfully integrated into civilian airspace. Of these obstacles the most pressing deal with safety such as obstacle avoidance, communication between manned and unmanned aircraft, and robust and fault tolerant systems. System identification (system ID) plays a key roll in making UAVs more robust and fault tolerant. Models of UAV dynamics can be determined through system ID. With accurate models, robust and fault tolerant controllers can be designed, simulated, and evaluated. Thus system ID is a valuable tool in increasing the safety and robustness of UAVs. In this discussion, a method of system ID is proposed, which utilizes least squares and adaptive online filtering. This method can be implemented while the UAV is in flight, making it possible to detect problems in flight. Results from this method of system ID on flight data is given. A future research direction is given with emphasis on the benefits and contributions to robust and fault tolerant systems.

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