A sampled-data extremum-seeking approach for accurate setpoint control of motion systems with friction

Leroy Hazeleger, Ruud Beerens, Nathan van de Wouw

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Samenvatting

This paper presents an extremum-seeking approach for accurate setpoint control of motion systems with friction, performing a repetitive motion. The classical PID controller, often used in industry for frictional motion systems, suffers from severe performance limitations. In particular, friction-induced limit cycling (hunting) is observed when integral control is employed on systems with unknown Stribeck friction, thereby compromising stability. Moreover, even if stability is warranted, transient performance highly depends on the particular frictional characteristic, which is typically uncertain. To deal with such uncertainty and to warrant optimal setpoint performance for the actual frictional properties, we propose a PID-based learning controller that achieves improved transient performance. Hereto, we consider a PID-type controller with a time-varying integral controller gain, which is adaptively obtained by employing a sampled-data extremum-seeking approach, resembling iterative learning control. The proposed approach does not require any knowledge on the friction characteristic. The working principle is illustrated by means of a representative simulation example.

Originele taal-2Engels
Pagina's (van-tot)801-806
Aantal pagina's6
TijdschriftIFAC-PapersOnLine
Volume52
Nummer van het tijdschrift16
DOI's
StatusGepubliceerd - sep 2019
Evenement11th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2019 - Vienna, Oostenrijk
Duur: 4 sep 20196 sep 2019

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