Optimal input design for system identification with quantized sensors is tackled in a worst-case setting. Under the assumption of uniformly quantized measurements, the paper addresses the one-step input design problem for static gains. Results are provided for both noise-free and noisy data and are instrumental for designing suboptimal inputs for FIR systems of arbitrary order. The input design problem over a time horizon of length N is also investigated, in order to characterize the time complexity of the considered identification problem.

Casini, M., Garulli, A., Vicino, A. (2009). Input design for worst-case system identification with uniformly quantized measurements. In Proceedings 15th IFAC Symposium on System Identification (pp.54-59). New York : IEEE [10.3182/20090706-3-FR-2004.0263].

Input design for worst-case system identification with uniformly quantized measurements

Casini, M.;Garulli, A.;Vicino, A.
2009-01-01

Abstract

Optimal input design for system identification with quantized sensors is tackled in a worst-case setting. Under the assumption of uniformly quantized measurements, the paper addresses the one-step input design problem for static gains. Results are provided for both noise-free and noisy data and are instrumental for designing suboptimal inputs for FIR systems of arbitrary order. The input design problem over a time horizon of length N is also investigated, in order to characterize the time complexity of the considered identification problem.
2009
978-390266147-0
Casini, M., Garulli, A., Vicino, A. (2009). Input design for worst-case system identification with uniformly quantized measurements. In Proceedings 15th IFAC Symposium on System Identification (pp.54-59). New York : IEEE [10.3182/20090706-3-FR-2004.0263].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/21840
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