Collocation-Based Output-Error Method for Aircraft System Identification

TL;DR

This paper introduces a collocation-based reformulation of the output-error method for aircraft system identification, enabling stable and efficient estimation even for unstable systems and with poor initial guesses.

Contribution

It presents a novel collocation-based approach to aircraft system identification that overcomes limitations of the traditional output-error method, especially for unstable systems.

Findings

Collocation reformulation works for unstable systems without modifications.

Convergence achieved even with poor initial guesses.

Method validated with simulated and real flight-test data.

Abstract

The output-error method is a mainstay of aircraft system identification from flight-test data. It is the method of choice for a wide range of applications, from the estimation of stability and control derivatives for aerodynamic database generation to sensor bias estimation in flight-path reconstruction. However, notable limitations of the output-error method are that it requires ad hoc modifications for applications to unstable systems and it is an iterative method which is particularly sensitive to the initial guess. In this paper, we show how to reformulate the estimation as a collocation problem, an approach common in other disciplines but seldomly used in flight vehicle system identification. Both formulations are equivalent in terms of having the same solution, but the collocation-based can be applied without modifications or loss of efficiency to unstable systems. Examples with simulated and real-world flight-test data also show that convergence to the optimum is obtained even with poor initial guesses.