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This paper presents an identification algorithm dedicated to the Modal Analysis of physical objects. This algorithm was specifically designed to process cases where short duration tests with multiple-input excitations are used to identify the system. To conform to these particular conditions, an iterative identification method was developed. It makes use of an appropriate parametrization of multivariable transfer functions based on structured matrix fractions. The identification problem is solved in the frequency domain using an output-error formulation. This paper details this algorithm which is evaluated on an example illustrative of the in-flight modal analysis of an aircraft.

This paper addresses the problem of the identification of multivariable linear systems from measured or estimated samples of the impulse response. Most techniques are based on a low rank approximation of a block-Hankel matrix computed by a truncated singular value decomposition. The main drawback of such approaches is that the block-Hankel structure is not preserved in the approximation. Therefore these methods do not actually perform a term-wise fitting on the samples of the impulse response. Since the beginning of the 1990s, several algorithms were proposed for computing low rank approximations that maintain the matrix structure. But the methods available up until now still include limitations. In this article, three general and equivalent solutions to this identification problem are proposed in the general case of multiple-input multiple-output (MIMO) systems. They derive from a specific parametrization and perform a term-wise minimization of a least squares criterion on the samples of the impulse response.

Due to the high flexibility of modern transportation aircraft, a precise knowledge of their aeroelastic behaviour is required to design the flight control system. For this purpose, an identification toolbox named Harrisa ® was developed at ONERA. It was extensively used by Airbus for the development of the A340-600. The requirements for the recent Airbus A380 increased tremendously concerning the size of the models to be identified. Efficient identification techniques had then to be worked out. This paper introduces EFERA an extremely rapid realization algorithm that is compatible with an interactive use on such large-scale systems.

Flutter flight tests is a crucial and feared phase of the flight test program of a new aircraft. The specific operational context of flutter surveillance implies the development of automatic and reliable tools operating in real-time. At ONERA, we recently developed a toolbox dedicated to data processing for flutter tests. It was used for the latest Airbus aircraft from the A340-600 up to the A380. In this article, we present the main procedure of the toolbox : the identification routine together with the graphical interfaces that were designed to help the operator to get a rapid knowledge of the identification results.