Tensor networks for MIMO LPV system identification

DOI10.1080/00207179.2018.1501515zbMath1436.93032OpenAlexW2884122657MaRDI QIDQ5221376

Bilal Gunes, Verhaegen, Michel, Jan-Willem van Wingerden

Publication date: 25 March 2020

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2018.1501515

zbMATH Keywords

identificationsubspace methodstime-varying systemsclosed-loop identificationLPV systemstensor trains

Mathematics Subject Classification ID

System identification (93B30) Multivariable systems, multidimensional control systems (93C35) Linear systems in control theory (93C05)

Related Items (2)

Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory ⋮ Closed-loop delta-operator-based subspace identification for continuous-time systems utilising the parity space

Cites Work

• Tensor-Train Decomposition
• Refined instrumental variable methods for identification of LPV Box-Jenkins models
• Modeling and identification of linear parameter-varying systems
• Subspace identification of bilinear and LPV systems for open- and closed-loop data
• Consistency analysis of subspace identification methods based on a linear regression approach
• Tensor network alternating linear scheme for MIMO Volterra system identification
• Predictor-Based Tensor Regression (PBTR) for LPV subspace identification
• Subspace identification of MIMO LPV systems using a periodic scheduling sequence
• The role of vector autoregressive modeling in predictor-based subspace identification
• On Local Convergence of Alternating Schemes for Optimization of Convex Problems in the Tensor Train Format
• The Alternating Linear Scheme for Tensor Optimization in the Tensor Train Format
• Tensor rank is NP-complete
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Kronecker products and matrix calculus in system theory
• Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem
• Generalized Vectorization, Cross-Products, and Matrix Calculus
• LPV control and full block multipliers

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