Identification of Multivariable Linear Parameter Varying Systems Based on Subspace Techniques

Verdult, Vincent and Verhaegen, Michel (2000) Identification of Multivariable Linear Parameter Varying Systems Based on Subspace Techniques. In: 39th IEEE Conference on Decision and Control, 2000, 12-15 December 2000, Sydney, Australia.

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Abstract:	Presents a subspace type of identification method for multivariable linear parameter-varying systems in state space representation with affine parameter dependence. It is shown that a major problem with subspace methods for this kind of systems is the enormous dimensions of the data matrices involved. To overcome the curse of dimensionality, we suggest to use only the most dominant rows of the data matrices in estimating the model. An efficient selection algorithm is discussed that does not require the formation of the complete data matrices, but can process them row by row
Item Type:	Conference or Workshop Item
Copyright:	©2000 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Robotics and Mechatronics (CE)
Link to this item:	http://purl.utwente.nl/publications/25651
Official URL:	http://dx.doi.org/10.1109/CDC.2000.912083
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