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Modelling a gas pipeline as a repetitive process: controllability, observability and stability.

, , and . Multidimens. Syst. Signal Process., 26 (4): 967-984 (2015)

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Identification of Bilinear Systems With White Noise Inputs: An Iterative Deterministic-Stochastic Subspace Approach., , and . IEEE Trans. Contr. Sys. Techn., 17 (5): 1145-1153 (2009)Boundary control of discrete repetitive processes with smoothing: controllability, observability and disturbance attenuation., , and . Multidimens. Syst. Signal Process., 26 (1): 145-158 (2015)Subspace system identification of separable-in-denominator 2-D stochastic systems., and . CDC/ECC, page 1491-1496. IEEE, (2011)A subspace algorithm for identifying 2-D CRSD systems with deterministic inputs., , , and . CDC/ECC, page 6457-6462. IEEE, (2011)Machine learning barycenter approach to identifying LPV state-space models., , , , and . ACC, page 6351-6356. IEEE, (2016)A Dynamic Mode Decomposition Approach With Hankel Blocks to Forecast Multi-Channel Temporal Series., and . IEEE Control. Syst. Lett., 3 (3): 739-744 (2019)Subspace algorithm for identifying bilinear repetitive processes with deterministic inputs., , , and . ECC, page 1057-1062. IEEE, (2016)LPV system identification using a separable least squares support vector machines approach., , , , , and . CDC, page 2548-2554. IEEE, (2014)Nash equilibrium with wave dynamics and boundary control., , and . nDS, page 1-6. IEEE, (2015)Deriving mechanical structures in physical coordinates from data-driven state-space realizations., , , and . ACC, page 1107-1112. IEEE, (2015)