Input design in worst-case system identification with quantized measurements

DOI10.1016/j.automatica.2012.08.016zbMath1255.93045OpenAlexW2021490080MaRDI QIDQ1932689

Marco Casini, Antonio Vicino, Andrea Garulli

Publication date: 21 January 2013

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2012.08.016

zbMATH Keywords

FIR modelsinput designset membership identificationquantized measurements\(n\) static gain problems\(N\)-step optimal input problemdesign with multiple sensor thresholdsequispaced thresholdsgeneric sensor threshold distributionimpulse response identification problemproblem of optimal input

Mathematics Subject Classification ID

System identification (93B30) Identification in stochastic control theory (93E12)

Related Items

Set-membership errors-in-variables identification of MIMO linear systems ⋮ A new kernel-based approach to system identification with quantized output data ⋮ Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds ⋮ A linear programming approach to online set membership parameter estimation for linear regression models ⋮ Input design in worst-case system identification with quantized measurements ⋮ Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs ⋮ FIR systems identification under quantized output observations and a large class of persistently exciting quantized inputs ⋮ Fixed-order FIR approximation of linear systems from quantized input and output data ⋮ Robust distributed maximum likelihood estimation with dependent quantized data ⋮ Identification of Wiener systems with quantized inputs and binary-valued output observations ⋮ On the optimal worst-case experiment design for constrained linear systems ⋮ Recursive algorithms for parameter estimation with adaptive quantizer

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