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Smooth Output Reconstruction for Linear Systems with Quantized Measurements
Author(s) -
Zhu Hongzhong,
Sugie Toshiharu,
Fujimoto Hiroshi
Publication year - 2015
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.950
Subject(s) - quantization (signal processing) , regularization (linguistics) , regular polygon , linear system , mathematics , convex optimization , algorithm , control theory (sociology) , computer science , mathematical optimization , artificial intelligence , mathematical analysis , geometry , control (management)
This paper presents a novel approach to reconstruct the output of linear systems in the case where the measured output is uniformly quantized. By fitting the quantized measurements with polynomials in a moving horizon manner, a smooth signal is reconstructed by solving a convex optimization problem with ℓ 1 ‐norm regularization. The quantization feature and the system models are taken into account in the optimization. A numerical example is given to show the excellent reconstruction performance of the proposed method. In addition, the proposed method is implemented in a high‐precision linear stage through DSP, and its effectiveness is verified through experiments using a real positioning system.