Stability analysis of quantized iterative learning control systems using lifting representation

DOI10.1002/acs.2767zbMath1375.93115OpenAlexW2605435739MaRDI QIDQ4591518

Xuhui Bu, Lizhi Cui, Zhongsheng Hou, Junqi Yang

Publication date: 17 November 2017

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2767

zbMATH Keywords

convergence analysisiterative learning controldata quantizationsupervector formulation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Discrete-time control/observation systems (93C55) Linear systems in control theory (93C05) Stability of control systems (93D99)

Related Items (7)

Unknown input observer design of switched systems based on iterative learning ⋮ Data‐driven iterative learning control using a uniform quantizer with an encoding–decoding mechanism ⋮ Predictive compensation based quantization iterative learning control for nonlinear nonaffine discrete‐time systems ⋮ Finite‐level uniformly quantized learning control with random data dropouts ⋮ A two-dimensional approach to iterative learning control with randomly varying trial lengths ⋮ Discrete Fourier transform based frequency characteristics of iterative learning control for linear discrete-time systems ⋮ Distributed point-to-point iterative learning control for multi-agent systems with quantization

This page was built for publication: Stability analysis of quantized iterative learning control systems using lifting representation