Abstract
This paper proposes a new identification method for continuous-time SISO linear time-invariant models, which does not require the prior knowledge about the system order. First, an appropriately filtered input/output signal is projected onto a finite dimensional signal subspace. Then, based on the projected data, the system order is determined through a nuclear norm minimization which takes account of both model simplicity and output prediction accuracy. Numerical examples are given to demonstrate the effectiveness of the proposed method. Fig. 1 SISO y(t) = P • (p)u(t) + η(t) 1 p u(t), y(t) TR 0008/13/4908–0763 c 2012 SICE
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CITATION STYLE
HAMANO, A., MARUTA, I., & SUGIE, T. (2013). Identification of Continuous-time Systems Based on Signal Projection and Nuclear Norm Minimization. Transactions of the Society of Instrument and Control Engineers, 49(8), 763–769. https://doi.org/10.9746/sicetr.49.763
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