Enhancing feedforward controller tuning via instrumental variables: with application to nanopositioning
From MaRDI portal
Publication:5280282
DOI10.1080/00207179.2016.1219921zbMath1366.93120OpenAlexW2482067891MaRDI QIDQ5280282
Tom Oomen, Dennis Bruijnen, Frank Boeren
Publication date: 20 July 2017
Published in: International Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207179.2016.1219921
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (2)
On‐line instrumental variable‐based feedforward tuning for non‐resetting motion tasks ⋮ Iterative tuning of feedforward controller with precise time-delay compensation for precision motion system
Cites Work
- Unnamed Item
- Unnamed Item
- System identification of complex and structured systems
- Optimal input design for direct data-driven tuning of model-reference controllers
- Data-driven controller design. The \(H_2\) approach.
- On the disturbance properties of high order iterative learning control algorithms
- Instrumental variable methods for closed-loop system identification
- Refined instrumental variable estimation: maximum likelihood optimization of a unified Box-Jenkins model
- A comparison of model-based and data-driven controller tuning
- Using basis functions in iterative learning control: analysis and design theory
- Refined instrumental variable methods of recursive time-series analysis Part II. Multivariable systems
- Refined instrumental variable methods of recursive time-series analysis Part III. Extensions
- Some observations on instrumental variable methods of time-series analysis
- Refined instrumental variable methods of recursive time-series analysis Part I. Single input, single output systems
- Should model-based inverse inputs be used as feedforward under plant uncertainty?
- On the design of ILC algorithms using optimization
This page was built for publication: Enhancing feedforward controller tuning via instrumental variables: with application to nanopositioning