Computationally‐Light Non‐Lifted Data‐Driven Norm‐Optimal Iterative Learning Control
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Publication:4576608
DOI10.1002/asjc.1569zbMath1391.93089OpenAlexW2626786463WikidataQ57582278 ScholiaQ57582278MaRDI QIDQ4576608
Shangtai Jin, Zhongsheng Hou, Ronghu Chi, Biao Huang
Publication date: 12 July 2018
Published in: Asian Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/asjc.1569
nonlinear discrete-time systemscomputationally-light algorithmdata-driven control approachnorm optimal ILC
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Related Items (7)
Data‐driven iterative learning control using a uniform quantizer with an encoding–decoding mechanism ⋮ Input–output‐driven gain‐adaptive iterative learning control for linear discrete‐time‐invariant systems ⋮ Markov parameters identification and adaptive iterative learning control for linear discrete-time MIMO systems with higher-order relative degree ⋮ Kernel-based regularized iterative learning control of repetitive linear time-varying systems ⋮ Predictive compensation based quantization iterative learning control for nonlinear nonaffine discrete‐time systems ⋮ Observer-based data-driven constrained norm optimal iterative learning control for unknown non-affine non-linear systems with both available and unavailable system states ⋮ Quantisation compensated data-driven iterative learning control for nonlinear systems
Cites Work
- Linear computational complexity robust ILC for lifted systems
- A computationally efficient norm optimal iterative learning control approach for LTV systems
- Norm-optimal iterative learning control with application to problems in accelerator-based free electron lasers and rehabilitation robotics
- A synthetic approach for robust constrained iterative learning control of piecewise affine batch processes
- A computationally efficient algorithm of iterative learning control for discrete-time linear time-varying systems
- Iterative learning control with initial rectifying action
- A numerical method for determining monotonicity and convergence rate in iterative learning control
- A structured matrix approach to efficient calculation of LQG repetitive learning controllers in the lifted setting
- Iterative learning control for discrete-time systems with exponential rate of convergence
- On the design of ILC algorithms using optimization
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