Semester

Fall

Date of Graduation

2002

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Marcello R. Napolitano.

Abstract

The contribution of this research effort was to show that a reliable RPV could be built, tested, and successfully used for flight testing and parameter estimation purposes, in an academic setting. This was a fundamental step towards the creation of an automated Unmanned Aerial Vehicle (UAV). This research project was divided into four phases. Phase one involved the construction, development, and initial flight of a Remotely Piloted Vehicle (RPV), the West Virginia University (WVU) Boeing 777 (B777) aircraft. This phase included the creation of an onboard instrumentation system to provide aircraft flight data. The objective of the second phase was to estimate the longitudinal and lateral-directional stability and control derivatives from actual flight data for the B777 model. This involved performing and recording flight test maneuvers used for analysis of the longitudinal and lateral-directional estimates. Flight maneuvers included control surface doublets produced by the elevator, aileron, and rudder controls. A parameter estimation program known as pEst, developed at NASA Dryden Flight Research Center (DFRC), was used to compute the off-line estimates of parameters from collected flight data. This estimation software uses the Maximum Likelihood (ML) method with a Newton-Raphson (NR) minimization algorithm. The mathematical model used a traditional static and dynamic derivative buildup. Phase three focused on comparing a linear model obtained from the phase two ML estimates, with linear models obtained from a (i) Batch Least Squares Technique (BLS) and (ii) a technique from the Matlab system identification toolbox. Historically, aircraft parameter estimation has been performed off-line using recorded flight data from specifically designed maneuvers. In recent years, several on-line parameter identification techniques have been evaluated for real-time on-line applications. Along this research line, a novel contribution of this work was to compare the off-line estimation results with results obtained using a recently introduced frequency based on-line estimation method. Specifically, phase four focused on comparing the ML results with a frequency domain based on-line estimation technique. The RPV vehicle and payload was designed and constructed with the combined efforts of WVU researchers, graduate and undergraduate students of the Mechanical and Aerospace Engineering Department, and a private sub-contractor, Craig Aviation.

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