System Identification of Unmanned Air Systems at Texas A&M University

Abstract

This paper presents a summary of system identification flight testing and results for a variety of large and small fixed-wing and multirotor unmanned air systems at Texas A&M University from 1999 to 2023. The six different types of vehicles range from a large powered parafoil, to a fixed-wing vehicle with synthetic jet-actuated roll control effectors, to a radially asymmetric multirotor, to large and small fixed-wing vehicles, and to a Steppe eagle. The observer/Kalman filter identification algorithm is used to generate linear time-invariant state-space models, and the results for both near-real-time online model generation and postflight offline model generation are presented. The use and efficacy of a variety of test input types and their sensitivity to exogenous inputs such as turbulence, in addition to identified model evaluation and selection criteria, are discussed. Several generations of low size, weight, power, and cost flight-test instrumentation including the Developmental Flight-Test Instrumentation data acquisition package are also presented. Challenges that arose from the flight-testing campaigns along with solutions are highlighted in the paper.