A 2D systems approach to iterative learning control for discrete linear processes with zero Markov parameters

DOI10.1080/00207179.2011.575799zbMath1230.93103OpenAlexW2037922776MaRDI QIDQ3098193

Krzysztof Gałkowski, Zhonglun Cai, Chris T. Freeman, Lukasz Hladowski, Paul L. Lewin, Eric Rogers

Publication date: 17 November 2011

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://eprints.soton.ac.uk/272145/1/ijcrev.pdf

zbMATH Keywords

iterative learning controlexperimental verificationrepetitive process

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Discrete-time control/observation systems (93C55) Linear systems in control theory (93C05) Stochastic learning and adaptive control (93E35)

Related Items (5)

Robust finite frequency \(H_\infty \) filtering for uncertain 2-D systems: the FM model case ⋮ A convex optimization approach to robust iterative learning control for linear systems with time-varying parametric uncertainties ⋮ Control law design for discrete linear repetitive processes with non-local updating structures ⋮ A 2D Hopfield neural network approach to mechanical beam damage detection ⋮ \(H_\infty\) ILC design for discrete linear systems with packet dropouts and iteration-varying disturbances

Cites Work

• Further results on the experimental evaluation of iterative learning control algorithms for non-minimum phase plants
• A discrete state-space model for linear image processing
• A robust high-order P-type iterative learning controller using current iteration tracking error
• Iterative learning control synthesis based on 2-D system theory
• P-type iterative learning control for systems that contain resonance

This page was built for publication: A 2D systems approach to iterative learning control for discrete linear processes with zero Markov parameters