Designing an Iterative Learning Control Algorithm Based on Process History using limited post process geometrical information

Benny Ørtoft Endelt, Wolfram Volk

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstrakt

Feedback control of sheet metal forming operations has been an active research field the
last two decades and highly advanced control algorithms have been proposed - controlling both the total
blank-holder force and in some cases also the distribution of the blank-holder force. However, there is a
number of obstacles which need to be addressed before an industrial implementation is possible, e.g. the
proposed control algorithms are often limited by the ability to sample process data with both sufficient
accuracy and robustness - this lack of robust sampling technologies is one of the main barriers preventing
successful industrial implementation. Secondly limitation in the current press designs; many of the presses
currently used in industry only offer limited opportunities to change the blank-holder force during the punch
stroke. Even if the press has the opportunity to change the blank-holder force, the reaction speed may be
insufficient compared to the production rate in an industrial application. We propose to design an iterative
learning control (ILC) algorithm which can control and update the blank-holder force as well as the
distribution of the blank-holder force based on limited geometric data from previously produced parts. The
proposed algorithm was exemplarily tested on a square cup.
OriginalsprogEngelsk
TitelIDDRG 2013 Conference Proceedings Towards Zero Failure Production Methods by Advanced Modeling Techniques and a Process Integrated Virtual control
Publikationsdato2013
Sider69-74
ISBN (Trykt)978-3-906031-34-1
StatusUdgivet - 2013
BegivenhedIDDRG 2013 Conference - Zurich, Schweiz
Varighed: 2 jun. 20135 jun. 2013

Konference

KonferenceIDDRG 2013 Conference
Land/OmrådeSchweiz
ByZurich
Periode02/06/201305/06/2013

Emneord

  • deep drawing, iterative learning control, run-2-run control, distributed blank-holder force, process control, process robustness, finite element.

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