Title :
Suboptimal algorithms for worst case identification in H∞ and model validation
Author_Institution :
Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA, USA
fDate :
8/1/1994 12:00:00 AM
Abstract :
New algorithms based on convex programming are proposed for worst case system identification. The algorithms are optimal within a factor of two asymptotically. Further, model validation, or data consistency, is embedded in the identification process. Explicit worst case identification error bounds in the H∞ norm are also derived for both uniformly and nonuniformly spaced frequency response samples
Keywords :
computational complexity; convex programming; frequency response; identification; H∞ norm; convex programming; data consistency; error bounds; frequency response; model validation; worst case identification; Computational complexity; Computer aided software engineering; Costs; Frequency response; H infinity control; Interpolation; Noise level; Noise robustness; Stability; System identification;
Journal_Title :
Automatic Control, IEEE Transactions on
