Parameter-optimal iterative learning control using polynomial representations of the inverse plant

DOI10.1080/00207179.2012.658867zbMath1256.93063OpenAlexW1996227160MaRDI QIDQ4905774

Bing Chu, Mutita Songjun, David H. Owens

Publication date: 20 February 2013

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

Full work available at URL: https://doi.org/10.1080/00207179.2012.658867

zbMATH Keywords

optimizationconvergenceapproximationpolynomialsiterative learning control

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Discrete-time control/observation systems (93C55)

Related Items (4)

Quasi-Newton-type optimized iterative learning control for discrete linear time invariant systems ⋮ Linearly monotonic convergence of nonlinear <scp>parameter‐optimal</scp> iterative learning control to linear discrete‐time‐invariant systems ⋮ Input–output‐driven gain‐adaptive iterative learning control for linear discrete‐time‐invariant systems ⋮ Fault detection of networked dynamical systems: a survey of trends and techniques

Cites Work

• Basis functions and parameter optimisation in high-order iterative learning control
• Modelling of non-minimum phase effects in discrete-time norm optimal iterative learning control
• Robust monotone gradient-based discrete-time iterative learning control
• Limit sets and switching strategies in parameter-optimal iterative learning control
• Predictive optimal iterative learning control
• Iterative learning control for discrete-time systems with exponential rate of convergence
• Parameter optimization in iterative learning control
• Iterative learning control using optimal feedback and feedforward actions
• Discrete-time inverse model-based iterative learning control: stability, monotonicity and robustness

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