Subspace identification of linear parameter-varying systems with innovation-type noise models driven by general inputs and a measurable white noise time-varying parameter vector

DOI10.1080/00207720802184741zbMath1194.93036OpenAlexW1972280794MaRDI QIDQ3625244

Paulo Lopes dos Santos, J. L. Martins de Carvalho, José A. Ramos

Publication date: 12 May 2009

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720802184741

zbMATH Keywords

subspace identificationlinear parameter-varying systemslinear deterministic-stochastic state-space approximations

Mathematics Subject Classification ID

System identification (93B30) Linear systems in control theory (93C05) Variable structure systems (93B12)

Related Items (6)

A convex relaxation approach to set-membership identification of LPV systems ⋮ Linear parameter-varying subspace identification: a unified framework ⋮ LPV system identification under noise corrupted scheduling and output signal observations ⋮ Towards efficient maximum likelihood estimation of LPV-SS models ⋮ Leakage detection and location in gas pipelines through an LPV identification approach ⋮ Identification of multi-input systems based on correlation techniques

Cites Work

• Identification of the deterministic part of MIMO state space models given in innovations form from input-output data
• 4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems
• Subspace identification of multivariable linear parameter-varying systems
• Kernel methods for subspace identification of multivariable LPV and bilinear systems
• Identification of linear parameter varying models
• Newton's Method for Discrete Algebraic Riccati Equations when the Closed-Loop Matrix Has Eigenvalues on the Unit Circle
• Identification of non-linear parametrically varying models using separable least squares

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