This paper discusses results related to approximate identification for robust control. The criteria for modeling and identification are formulated in terms of ℒ∞ or ℋ∞ norm. Emphasis is made on the construction of a model set by specifying bases in function spaces ℒ2, ℋ2 or in the disc algebra A. These bases include - besides the most widely used trigonometric basis-the recently introduced rational orthogonal bases and some wavelet bases. The construction of identification algorithms considered as bounded operators mapping measured noisy frequency response data to an element in the model space is discussed. Bounds on the operator norm effecting the approximation and the noise errors are given, too.
- Orthonormal basis
- Worst-case identification
ASJC Scopus subject areas
- Control and Systems Engineering