Data-driven model reference control design by prediction error identification
From MaRDI portal
Publication:1796640
DOI10.1016/j.jfranklin.2016.08.006zbMath1398.93071OpenAlexW2512923311MaRDI QIDQ1796640
Diego Eckhard, Michel Gevers, Lucíola Campestrini, Alexandre Sanfelice Bazanella
Publication date: 17 October 2018
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2016.08.006
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (3)
Quadratic Matrix Inequalities with Applications to Data-Based Control ⋮ Data‐assisted control: A framework development by exploiting NASA Generic Transport platform ⋮ Data-driven model reference control design by prediction error identification
Cites Work
- Virtual reference feedback tuning for non-minimum phase plants
- Data-driven controller design. The \(H_2\) approach.
- Virtual reference feedback tuning: A direct method for the design of feedback controllers
- Data-driven model reference control design by prediction error identification
- Necessary and sufficient conditions for uniqueness of the minimum in Prediction Error Identification
- On identification methods for direct data-driven controller tuning
- Asymptotic variance expressions for estimated frequency functions
- Iterative correlation‐based controller tuning
- Variance Error Quantifications That Are Exact for Finite-Model Order
This page was built for publication: Data-driven model reference control design by prediction error identification
