Numerical Comparison of Three Different Feedback Control Schemes Applied on a Forming Operation

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Feedback and process control of metalforming processes has received increasing attention the lastdecade. Basically there exist four control philosophies; control ofprocess parameters during the punch stroke, iterative learning control(based on historical data), a combination iterative learning andfeedback control and finally feed-forward control. The present work willpresent three different control schemes which all are based onfeedback philosophy i.e. control during the punch stroke or iterativelearning control, where process parameters are updated according toprocess history. The three control schemes are tested using a non-linear finite element model of a square deep-drawing and finallypros and cons are discussed based on the numerical results.

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Peter F. Pelz and Peter Groche

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64-74

Citation:

B. Endelt, "Numerical Comparison of Three Different Feedback Control Schemes Applied on a Forming Operation", Applied Mechanics and Materials, Vol. 885, pp. 64-74, 2018

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November 2018

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[1] B Endelt. Design strategy for optimal iterative learning control applied on a deep drawing process. International Journal of Advanced Manufacturing Technology, 88(1):3-18, (2017).

DOI: https://doi.org/10.1007/s00170-016-8501-z

[2] B. Endelt. Designing an iterative learning control algorithm based on process history - using limited post- process geometrical information. In Proceedings of the IDDRG 2017 Conference, (2017).

[3] B. Endelt and J. Danckert. Iterative learning and feedback control applied on a deep drawing process. International Journal of Material Forming, 3(SUPPL. 1):25-28, (2010).

DOI: https://doi.org/10.1007/s12289-010-0698-z

[4] B. Endelt and W. Volk. Designing an iterative learning control algorithm based on process history using limited post- process geometrical information. In Proceedings of the IDDRG 2013 Conference, Best in Class Stamping, 2013. submitted for presentation at the IDDRG 2013 Conference.

[5] Benny Endelt, Søren Tommerup, and Joachim Danckert. A novel feedback control system - controlling the material flow in deep drawing using distributed blank-holder force. Journal of Materials Processing Technology, 213(1):36 - 50, (2013).

DOI: https://doi.org/10.1016/j.jmatprotec.2012.08.003

[6] Jörg Heingärtner, Anja Neumann, Dirk Hortig, Yasar Rencki, and Pavel Hora. Acquisition of material properties in production for sheet metal forming processes. In AIP Conference Proceedings, volume 1567, pages 671-674. AIP, (2013).

DOI: https://doi.org/10.1063/1.4850061

[7] Yongseob Lim, Ravinder Venugopal, and A. Galip Ulsoy***. Advances in the control of sheet metal forming. In Proceedings of the 17th World Congress The International Federation of Automatic Control, (2008).

DOI: https://doi.org/10.1115/isfa2012-7117

[8] Sy-Wei Lo and Tsu-Chang Yang. Closed-loop control of the blank holding force in sheet metal forming with a new embedded-type displacement sensor. The International Journal of Advanced Manufacturing Technology, 24(7-8):553-559, (2004).

DOI: https://doi.org/10.1007/s00170-003-1711-1

[9] James A. Polyblank, Julian M. Allwood, and Stephen R. Duncan. Closed-loop control of product properties in metal forming: A review and prospectus. Journal of Materials Processing Technology, 214(11):2333 - 2348, (2014).

DOI: https://doi.org/10.1016/j.jmatprotec.2014.04.014

[10] K. Siegert, M. Ziegler, and S. Wagner. Closed loop control of the friction force. deep drawing process. Journal of Materials Processing Technology, 71(1):126-133, (1997).

DOI: https://doi.org/10.1016/s0924-0136(97)00158-1