Higher-order iterative learning control algorithms for linear systems

DOI10.1134/S0965542524700064MaRDI QIDQ6552615

P. V. Pakshin, Mikhail Emelianov, Julia Emelianova

Publication date: 10 June 2024

Published in: Computational Mathematics and Mathematical Physics (Search for Journal in Brave)

zbMATH Keywords

stabilityconvergencelinear systemslinear matrix inequalitieshigher-order algorithmsiterative learning controlvector Lyapunov functionrepetitive processes

Mathematics Subject Classification ID

Computer science (68-XX) Systems theory; control (93-XX)

Cites Work

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• Dissipativity and stabilization of nonlinear repetitive processes
• Control systems theory and applications for linear repetitive processes.
• Analysis of a high-order iterative learning control algorithm for uncertain nonlinear systems with state delays
• Analytic design of controls from root indicators
• Stability analysis of high-order iterative learning control for a class of nonlinear switched systems
• Iterative learning control. Robustness and monotonic convergence for interval systems.
• Higher-order iterative learning control algorithm
• Optimality of First-Order ILC Among Higher Order ILC
• Some methods of speeding up the convergence of iteration methods
• Design of optimal control systems with prescribed eigenvalues†

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