Willems’ Fundamental Lemma for State-Space Systems and Its Extension to Multiple Datasets
暂无分享,去创建一个
[1] Bart De Moor,et al. A note on persistency of excitation , 2005, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).
[2] Hong Ye,et al. Scheduling of networked control systems , 2001 .
[3] Rik Pintelon,et al. Identification of Linear Time-Invariant Systems From Multiple Experiments , 2015, IEEE Transactions on Signal Processing.
[4] Paolo Rapisarda,et al. Data-driven control: A behavioral approach , 2017, Syst. Control. Lett..
[5] Bart De Moor,et al. Algorithms for deterministic balanced subspace identification , 2005, Autom..
[6] Pietro Tesi,et al. Data-driven Linear Quadratic Regulation via Semidefinite Programming , 2019, IFAC-PapersOnLine.
[7] John Lygeros,et al. Data-Enabled Predictive Control for Grid-Connected Power Converters , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).
[8] Paolo Rapisarda,et al. On the linear quadratic data-driven control , 2007, 2007 European Control Conference (ECC).
[9] Bart De Moor,et al. Subspace Identification for Linear Systems: Theory ― Implementation ― Applications , 2011 .
[10] B. De Moor,et al. State Representations From Finite Time Series , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.
[11] Paolo Rapisarda,et al. Data-driven simulation and control , 2008, Int. J. Control.
[12] Pietro Tesi,et al. Formulas for Data-Driven Control: Stabilization, Optimality, and Robustness , 2019, IEEE Transactions on Automatic Control.
[13] Robert R. Bitmead,et al. Subspace Identification with Multiple Data Records: unlocking the archive , 2017, ArXiv.
[14] J. Willems,et al. DATA DRIVEN SIMULATION WITH APPLICATIONS TO SYSTEM IDENTIFICATION , 2005 .
[15] V. Verdult,et al. Filtering and System Identification: A Least Squares Approach , 2007 .
[16] Pietro Tesi,et al. Data-based guarantees of set invariance properties , 2019, IFAC-PapersOnLine.
[17] Frank Allgöwer,et al. A trajectory-based framework for data-driven system analysis and control , 2019, 2020 European Control Conference (ECC).
[18] John Lygeros,et al. Data-Enabled Predictive Control: In the Shallows of the DeePC , 2018, 2019 18th European Control Conference (ECC).
[19] Ivan Markovsky,et al. Structured Low-Rank Approximation with Missing Data , 2013, SIAM J. Matrix Anal. Appl..
[20] Ivan Markovsky. Exact system identification with missing data , 2013, 52nd IEEE Conference on Decision and Control.
[21] Ivan Markovsky,et al. The most powerful unfalsified model for data with missing values , 2016, Syst. Control. Lett..
[22] M. Kanat Camlibel,et al. Data Informativity: A New Perspective on Data-Driven Analysis and Control , 2019, IEEE Transactions on Automatic Control.
[23] Frank Allgöwer,et al. Data-Driven Model Predictive Control With Stability and Robustness Guarantees , 2019, IEEE Transactions on Automatic Control.
[24] I. Markovsky. A software package for system identification in the behavioral setting , 2013 .
[25] Ivan Markovsky,et al. A Missing Data Approach to Data-Driven Filtering and Control , 2017, IEEE Transactions on Automatic Control.
[26] Patrick Dewilde,et al. Subspace model identification Part 1. The output-error state-space model identification class of algorithms , 1992 .