Overview of System Identification Tool Advancements at Systems Technology, Incorporated

Abstract

For nearly two decades, Systems Technology, Inc. has been investigating novel system identification methods and practical applications. Two such methods will be highlighted herein: 1) the use of wavelet-based scalograms to explore the nature of dynamic systems in both the time and frequency domains simultaneously; and 2) a method to estimate frequency, damping, and mode shapes for lightly damped aeroelastic modes exhibited across a variety of air vehicles. From past work, two scalogram-based metrics have evolved, which are the power frequency and inceptor peak power phase, that will be one focus of this paper. The power frequency provides a metric that considers not only the dominant frequencies of the signal of interest, such as the command input from a pilot, but also the power at those frequencies. For the inceptor peak power phase, scalograms are used to identify the peak input power of a pilot’s inceptor command signal that when compared against a pitch or roll rate phase angle at the peak frequency produces a new method to detect the onset of pilot-induced oscillations. This paper will further describe system identification tools that extract modal information of aeroelastic vibrations observed in flight. Because it is often difficult to obtain input excitation data, particularly in real time, Systems Technology, Inc. developed a modal identification software toolbox that provides an innovative approach based on curve-fitting frequency domain decomposition, which relies only on output sensor data to identify the aeroelastic modes. Flight-test data are used to demonstrate the effectiveness and efficacy of the system identification approaches.