Rational Basis Functions in Iterative Learning Control for Multivariable Systems

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Samenvatting

Feedforward control with task flexibility for MIMO systems is essential to meet ever-increasing demands on throughput and accuracy. The aim of this paper is to develop a framework for data-driven tuning of rational feedforward controllers in iterative learning control (ILC) for noncommutative MIMO systems. A convex optimization problem in ILC is achieved by rewriting the nonlinear terms in the control scheme as a function of the previous feedforward parameters. A simulation study on an multivariable industrial printer shows that the developed framework converges and achieves significant better performance than direct application of the RBF algorithm using SK-iterations for SISO systems.
Originele taal-2Engels
Titel2023 62nd IEEE Conference on Decision and Control, CDC 2023
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's4644-4649
Aantal pagina's6
ISBN van elektronische versie979-8-3503-0124-3
DOI's
StatusGepubliceerd - 19 jan. 2024
Evenement2023 62nd IEEE Conference on Decision and Control (CDC) - Singapore, Singapore
Duur: 13 dec. 202315 dec. 2023
Congresnummer: 62

Congres

Congres2023 62nd IEEE Conference on Decision and Control (CDC)
Verkorte titelCDC 2023
Land/RegioSingapore
StadSingapore
Periode13/12/2315/12/23

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