Restricted complexity estimation is a major topic in control-oriented identification. Conditional algorithms are used to identify linear finite-dimensional models of complex systems, the aim being to minimize the worst-case identification error. High computational complexity of optimal solutions suggests employing suboptimal estimation algorithms. The paper studies different classes of conditional estimators and provides results that assess the reliability level of suboptimal algorithms.

Garulli, A., Kacewicz, B.Z., Vicino, A., Zappa, G. (2000). Error bounds for conditional algorithms in restricted complexity set membership identification. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 45(1), 160-164 [10.1109/9.827376].

Error bounds for conditional algorithms in restricted complexity set membership identification

GARULLI, ANDREA;VICINO, ANTONIO;
2000-01-01

Abstract

Restricted complexity estimation is a major topic in control-oriented identification. Conditional algorithms are used to identify linear finite-dimensional models of complex systems, the aim being to minimize the worst-case identification error. High computational complexity of optimal solutions suggests employing suboptimal estimation algorithms. The paper studies different classes of conditional estimators and provides results that assess the reliability level of suboptimal algorithms.
2000
Garulli, A., Kacewicz, B.Z., Vicino, A., Zappa, G. (2000). Error bounds for conditional algorithms in restricted complexity set membership identification. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 45(1), 160-164 [10.1109/9.827376].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/3668
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