Subspace identification is a well known and robust technique to identify linear models. It is less known that efficient recursive implementations exist for subspace algorithms. Over the last few years, several recursive input-output subspace algorithms have been proposed which mainly follow the following two steps:
Replace the QR decomposition which is usually the first step of a subspace implementation by a recursive QR decomposition. Note that only R is needed in classical subspace algorithms. The same remains true for the recursive algorithms which is a big asset.
Replace the SVD decomposition by a subspace tracking algorithm. Efficient implementations have been obtained.
In our research, we deal with recursive output-only algorithms and recursive stochastic realization on the one hand and input-output recursive algorithms applied to data from airplanes on the other hand. More information can be found in Goethals I., Mevel L., Benveniste A., De Moor B. Recursive output-only subspace identification for in-flight flutter monitoring, in Proc. of the 22nd International Modal Analysis Conference (IMAC-XXII), Dearborn, Michigan, Jan. 2004 and De Cock K., Mercère G., De Moor B., Recursive subspace identification for in-flight modal analysis of airplanes, in Proc. of the International Conference on Noise and Vibration Engineering (ISMA 2006), Leuven, Belgium, Sept. 2006, pp. 1563-1577.
Researcher(s): Katrien De Cock