Real-Time Parameter Estimation in the Frequency Domain

Abstract

A method for real-time estimation of parameters in a linear dynamic state space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight for indirect adaptive or reconfigurable control. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle (HARV) were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than 1 cycle of the dominant dynamic mode natural frequencies, using control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements, and could be implemented aboard an aircraft in real time. Nomenclature A, B,C, Dsystem matrices E ; @

System Identification of Small Unmanned Aerial Vehicle Flight Characteristics Issue I: Evaluation of Measurement Avionics and Analytical Methods

“…In other words, FTR handles the frequency-series data, while RLS manages the time-series data. According to Morelli,14) the following are the main advantages of FTR: 1) Robustness against both process and measurement noise because of its frequency filtering and 2) ease of removing the biases, that is, trimming values that are not required for the estimation, by filtering out the zero-Hz information. Its significant disadvantages for this study are also summarized in two points: FTR requires data in which the target system is sufficiently and periodically excited, and the trim values are assumed to be stable, otherwise, the estimation degrades tremendously.…”

Adaptive LFT control of a civil aircraft with online frequency‐domain parameter estimation

“…Furthermore, the availability of efficient tools making the transition from TD to FD possible, such as the recursive Fourier transform (FT), greatly facilitates their use, and this was stressed in many publications during the last 20 years. 41,[43][44][45][46][47][48] Figure 1 gives a schematic representation of the way the FD information is linked to the estimation process. Moreover, many issues specific to online estimation are mitigated when using FD approaches instead of TD ones.…”

“…That is why we look for a simple enough approach, likely to satisfy those real-time constraints, and based on a fully recursive algorithm. At first, it should be noticed that summation (5) makes very simple operations possible (see the work of Morelli, 45…”

Real-Time Dynamic Modeling: Data Information Requirements and Flight-Test Results

“…Several methods [1][2][3][4][5] have been investigated for identifying local linear dynamic models from flight data in real time. One of these methods [4,6] is based on a recursive Fourier transform and equation-error modeling in the frequency domain. This method, sometimes called the Fourier transform regression (FTR) method, produces very accurate results with valid error measures and has many practical advantages.…”

“…The FTR method has been successfully applied [4,[6][7][8][9][10][11]] to identify accurate linear dynamic models in real time at individual flight conditions. Although this capability is important and useful, further progress requires that this capability be extended to continuous application as the aircraft flies through a wide range of changing flight conditions throughout the flight envelope.…”