Virtual commissioning for the control of the continuous industrial processes — Case study

This paper concentrates on the possibilities of the application of the virtual commissioning procedure for the design and verification of the control systems for the continuous industrial processes. After short review and defining the motivation and recognizing the bottlenecks, the case study is presented. It is based on the laboratory pneumatic setup representing the nonlinear continuous process of the higher relative degree. The stages of its modeling are presented and the potential possibilities of the application of the virtual commissioning for its control are discussed, based on the practical results.

[1]  Bogdan Gabrys,et al.  Linearizing controller for higher-degree nonlinear processes with compensation for modeling inaccuracies practical validation and future developments , 2014, 2014 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO).

[2]  Tomasz Klopot,et al.  Flexible function block implementation of the balance-based adaptive controller as the potential alternative for PID-based industrial applications , 2014 .

[3]  Reimar Schumann,et al.  Virtual Commissioning Of Manufacturing Systems A Review And New Approaches For Simplification , 2010, ECMS.

[4]  Witold Klopot,et al.  Flexible function block for PLC-based implementation of the Balance-Based Adaptive Controller , 2012, 2012 American Control Conference (ACC).

[5]  Markus Bregulla,et al.  Representative Vector Method for modeling of energy consumption for the assembly line , 2013, 2013 18th International Conference on Methods & Models in Automation & Robotics (MMAR).

[6]  Sebastian Budzan.  Fusion of Visual and Range Images for Object Extraction , 2014, ICCVG.

[7]  Rhinehart.  The century's greatest contributions to control practice , 2000, ISA transactions.

[8]  Chang Ho Lee,et al.  Simulation framework for the verification of PLC programs in automobile industries , 2011 .

[9]  Sang C. Park,et al.  Survey on the virtual commissioning of manufacturing systems , 2014, J. Comput. Des. Eng..

[10]  Edward Hrynkiewicz,et al.  An idea of event-driven program tasks execution , 2009, PDeS.

[11]  Jacek Czeczot,et al.  On possibilities of the practical implementation of balance-based adaptive control methodology , 2007 .

[12]  Bogdan Gabrys,et al.  Review of adaptation mechanisms for data-driven soft sensors , 2011, Comput. Chem. Eng..

[13]  Costas Kravaris,et al.  Advances and selected recent developments in state and parameter estimation , 2013, Comput. Chem. Eng..

[14]  Zhiqiang Gao,et al.  Theory vs. practice: the challenges from industry , 2004, Proceedings of the 2004 American Control Conference.

[15]  G Valencia-Palomo,et al.  Programmable logic controller implementation of an auto-tuned predictive control based on minimal plant information. , 2011, ISA transactions.

[16]  Ian K. Craig,et al.  Economic assessment of advanced process control – A survey and framework , 2008 .

[17]  Roderick Murray-Smith,et al.  Multiple Model Approaches to Modelling and Control , 1997 .

[18]  YangQuan Chen,et al.  Modeling, Analysis And Design Of Control Systems In Matlab And Simulink , 2014 .

[19]  Michal Fratczak,et al.  Simplified modeling of plate heat exchangers , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).