System Identification for Small Flying-Wing Unmanned Aircraft Using Open-loop and Closed-loop Flight Data

Abstract

Small unmanned aircraft systems face unique challenges in system identification due to their light weight, small size, and increased sensitivity to wind and gusts. To address these challenges, flight test procedures for sUAS system identification using open-loop and closed-loop flight data are presented. The approaches are demonstrated through system identification of a small flying-wing UAS equipped with a low-cost Pixhawk autopilot. The open-loop method is demonstrated through identification of the longitudinal bare-airframe aircraft dynamics. Longitudinal frequency responses were estimated from the open-loop flight data, and a linear state space model was identified from the estimated frequency responses and supplemental trim data, which was used to better identify parameters related to the low-frequency phugoid mode. The identified phugoid mode matches well with low-frequency oscillations measured from flight data in the time domain. The closed-loop method is demonstrated through identification of the lateral-directional dynamics. This approach is shown to improve signal-to-noise ratio and reduce deviation from the reference flight condition, which improves modeling results, and it can be used to simultaneously identify the bare-airframe, closed-loop, and broken-loop UAS dynamics from the same set of closed-loop flight data, reducing time and efforts spent flight testing. The identified lateral-directional model is compared with closed- and broken-loop frequency responses estimated from flight data. The results show excellent agreement, with all computed metrics, such as stability margins, matching within 10%, demonstrating the effectiveness of this method.