Noniterative tensor network‐based algorithm for Volterra system identification
DOI10.1002/rnc.6104zbMath1528.93029OpenAlexW4220713537WikidataQ114234671 ScholiaQ114234671MaRDI QIDQ6063766
Raymond A. de Callafon, Yangsheng Hu, Li Tan
Publication date: 12 December 2023
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.6104
persistent excitationVolterra seriesnonlinear system identificationlow-rank approximationstensor network
System identification (93B30) Nonlinear systems in control theory (93C10) Multivariable systems, multidimensional control systems (93C35) Algebraic methods (93B25)
Cites Work
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- Tensor-Train Decomposition
- Fundamental tensor operations for large-scale data analysis using tensor network formats
- Decoupling the linear and nonlinear parts in Hammerstein model identification
- Tensor network subspace identification of polynomial state space models
- Robust identification of OE model with constrained output using optimal input design
- A tensor network Kalman filter with an application in recursive MIMO Volterra system identification
- Tensor network alternating linear scheme for MIMO Volterra system identification
- Stable Gaussian process based tracking control of Euler-Lagrange systems
- Nonlinear black-box modeling in system identification: A unified overview
- Variance reduction in covariance based realization algorithm with application to closed-loop data
- A convex approach for NMPC based on second order Volterra series models
- Nonlinear predictive control of smooth nonlinear systems based on Volterra models. Application to a pilot plant
- Filtering and System Identification
- Experimental design and identifiability for non-linear systems
- Application and comparison of different identification schemes under industrial conditions
- Efficient Computation of Bilinear Approximations and Volterra Models of Nonlinear Systems
- Adaptive optimization algorithm for nonlinear Markov jump systems with partial unknown dynamics
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