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A. Janot. (2021) A Separable Instrumental Variable Method for Robot Identification. A Separable Instrumental Variable Method for Robot Identification.
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V. Cerone, D. Piga, D. Regruto & R. Tóth. (2012) Input-output LPV model identification with guaranteed quadratic stability. IFAC Proceedings Volumes 45:16, pages 1767-1772.
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V. Cerone, D. Piga, D. Regruto & R. Toth. (2012) Minimal LPV state-space realization driven set-membership identification. Minimal LPV state-space realization driven set-membership identification.
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Janusz P. Papliński. (2009) Hybrid Genetic and Nelder-Mead Algorithms for Identification of Time Delays. IFAC Proceedings Volumes 42:13, pages 443-448.
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F. Previdi & M. Lovera. (2009) Identification of parametrically-varying models for the rainfall-runoff relationship in urban drainage networks. IFAC Proceedings Volumes 42:10, pages 1768-1773.
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C. Novara, F. Ruiz & M. Milanese. (2008) Direct identification of optimal filters for LPV systems. Direct identification of optimal filters for LPV systems.
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Giovanna Castillo Estrada, Harald Kirchsteiger & Luigi del Re. (2008) Compact representation of a nonlinear system using the NLPV approach. Compact representation of a nonlinear system using the NLPV approach.
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Federico Felici, Jan-Willem van Wingerden & Michel Verhaegen. (2007) Subspace identification of MIMO LPV systems using a periodic scheduling sequence. Automatica 43:10, pages 1684-1697.
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Xiukun Wei & Luigi del Re. (2007) Gain Scheduled $H_{\infty}$ Control for Air Path Systems of Diesel Engines Using LPV Techniques. IEEE Transactions on Control Systems Technology 15:3, pages 406-415.
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H. Jonsdottir, H. Aa Nielsen, H. Madsen, J. Eliasson, O. P. Palsson & M. K. Nielsen. (2007) Conditional parametric models for storm sewer runoff. Water Resources Research 43:5.
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Tomohiro Hachino & Visakan Kadirkamanathan. (2007) Time Series Forecasting Using Multiple Gaussian Process Prior Model. Time Series Forecasting Using Multiple Gaussian Process Prior Model.
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P.C. Young & H. Garnier. (2006) Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems. Environmental Modelling & Software 21:8, pages 1055-1072.
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