Iterative learning control for spatio-temporal dynamics using Crank-Nicholson discretization
DOI10.1007/S11045-010-0132-1zbMath1255.93051OpenAlexW2051364866MaRDI QIDQ1937797
Krzysztof Gałkowski, Błażej Cichy, Eric Rogers
Publication date: 1 February 2013
Published in: Multidimensional Systems and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://eprints.soton.ac.uk/272473/1/mdsspcickilc.pdf
linear matrix inequalitiesiterative learning controlcontrol lawsfinite number of pointsbi-variate partial differential equationsCrank-Nicholson discretizationspatio-temporal systems
Learning and adaptive systems in artificial intelligence (68T05) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06)
Related Items (17)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An iterative learning algorithm for boundary control of a stretched moving string
- Stability of damped membranes and plates with distributed inputs
- A discrete state-space model for linear image processing
- Doubly-indexed dynamical systems: State-space models and structural properties
- Iterative learning control synthesis based on 2-D system theory
This page was built for publication: Iterative learning control for spatio-temporal dynamics using Crank-Nicholson discretization