An industrially relevant formulation of a distributed model predictive control algorithm based on minimal process information
•A novel formulation for DMPC architecture with input–output model.•Industrial considerations given through complexity simplifications in the design.•Robustness to modelling errors caused by main dynamics approximations. Plant-wide control implies advanced supervisory algorithms to maintain desired...
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| Veröffentlicht in: | Journal of process control Jg. 68; S. 240 - 253 |
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01.08.2018
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| ISSN: | 0959-1524, 1873-2771 |
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| Abstract | •A novel formulation for DMPC architecture with input–output model.•Industrial considerations given through complexity simplifications in the design.•Robustness to modelling errors caused by main dynamics approximations.
Plant-wide control implies advanced supervisory algorithms to maintain desired performance in the involved coupled sub-systems. The dynamical interactions among these sub-systems can vary with the operating point, material properties and disturbances present in the process. Recirculating loops introduce additional phenomena in the dynamic response, further challenging the control tasks. Complex process dynamics may be linear parameter varying (LPV) and may be difficult, if not impossible, to identify properly. In this context, maintaining global performance is a challenge one must undertake with limited information at hand. This paper investigates the trade-off between the complexity of the implementation and achieved performance, using supervisory predictive control with limited information shared, applied on a test-bench representative for process control industry. The robustness of the proposed algorithms is tested against a nominal scenario in which the prediction model is fully identified, with complete information exchange. Experimental tests are performed on a test-bench process characterized by strong interactions, and the results illustrate the usefulness of this work. |
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| AbstractList | •A novel formulation for DMPC architecture with input–output model.•Industrial considerations given through complexity simplifications in the design.•Robustness to modelling errors caused by main dynamics approximations.
Plant-wide control implies advanced supervisory algorithms to maintain desired performance in the involved coupled sub-systems. The dynamical interactions among these sub-systems can vary with the operating point, material properties and disturbances present in the process. Recirculating loops introduce additional phenomena in the dynamic response, further challenging the control tasks. Complex process dynamics may be linear parameter varying (LPV) and may be difficult, if not impossible, to identify properly. In this context, maintaining global performance is a challenge one must undertake with limited information at hand. This paper investigates the trade-off between the complexity of the implementation and achieved performance, using supervisory predictive control with limited information shared, applied on a test-bench representative for process control industry. The robustness of the proposed algorithms is tested against a nominal scenario in which the prediction model is fully identified, with complete information exchange. Experimental tests are performed on a test-bench process characterized by strong interactions, and the results illustrate the usefulness of this work. |
| Author | Ionescu, Clara M. Maxim, Anca Copot, Dana De Keyser, Robin |
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| Cites_doi | 10.1016/j.automatica.2016.02.009 10.1016/j.compchemeng.2012.05.011 10.1016/j.conengprac.2013.10.003 10.1016/j.sysconle.2010.06.005 10.1080/00207179.2012.679972 10.1002/oca.2141 10.1007/s11760-012-0322-4 10.1002/rnc.3640 10.1080/00207170802187247 10.1016/j.jprocont.2009.02.003 10.1109/MCS.2016.2621479 10.1007/s10877-013-9535-5 10.1016/0005-1098(81)90092-3 10.1016/j.automatica.2012.03.020 10.1016/j.compchemeng.2016.03.001 10.1016/j.solener.2008.11.005 10.1109/MCS.2016.2621438 10.1016/0005-1098(88)90024-6 10.1016/j.jprocont.2006.10.010 10.1016/j.jprocont.2006.10.011 10.1016/j.jprocont.2015.11.002 10.1109/TII.2016.2532118 |
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| References | R. De Keyser, J. Donald III, Z. Lu, H. De Waard, MPC in semiconductor processing, MPC in thermal processing, USA Patents (08/597-438, 6207936,6373033). De Keyser, Van de Velde, Dumortier (bib0100) 1988; 24 Hermans, Jokić, Lazar, Alessio, van den Bosch, Hiskens, Bemporad (bib0045) 2012; 85 Soltesz, Mercader, Baños (bib0155) 2016; 27 Bauer, Horch, Xie, Jelali, Thornhill (bib0005) 2016; 38 Ionescu, Nascu, Ltdc:De Keyser:rtdc (bib0115) 2014; 28 Pop, Ionescu, De Keyser, Dulf (bib0165) 2012; 6 Quijano, Ocampo-Martinez, Barreiro-Gomez, Obando, Pantoja, Mojica-Nava (bib0080) 2017; 37 De Keyser, Ionescu (bib0140) 2003 Wang (bib0145) 2009 Dutta, Hartley, Maciejowski, De Keyser (bib0175) 2014 Camacho, Bordons (bib0150) 1999 Maciejowski (bib0170) 2000 Samad (bib0010) 2017; 37 Dutta, Depraetere, Ionescu, Pinte, Swevers, De Keyser (bib0110) 2014; 22 Davison, Aghdam (bib0020) 2010 Muros, Algaba, Maestre, Camacho (bib0075) 2016 Bodenburg, Lunze (bib0070) 2016 Dutta, Ionescu, De Keyser (bib0135) 2015; 36 Samad, McLaughlin, Lu (bib0015) 2007; 17 Farina, Scattolini (bib0055) 2012; 48 Folea, Mois, Muresan, Miclea, De Keyser, Cirstea (bib0130) 2016; 12 Kalsi, Lian, Żak (bib0025) 2009; 82 De Keyser, Van Cauwenberghe (bib0095) 1981; 17 De Keyser (bib0105) 2003 Scattolini (bib0040) 2009; 19 Ionescu, Muresan, Copot, De Keyser (bib0160) 2016 Maxim, Copot, De Keyser, Ionescu (bib0185) 2017 Christofides, Scattolini, Munoz de la Peña, Liu (bib0035) 2013; 51 Farina, Ferrari, Manenti, Pizzi (bib0065) 2016; 89 Alessio, Bemporad (bib0030) 2007 Conte, Jones, Morari, Zeilinger (bib0050) 2016; 69 Engell (bib0180) 2007; 17 Maestre, Negenborn (bib0085) 2014 Negenborn, Maestre (bib0090) 2014; 34 Ltdc:Gá:rtdclvez-Carrillo, Ltdc:De Keyser:rtdc, Ionescu (bib0120) 2009; 83 Stewart, Venkat, Rawlings, Wright, Pannocchia (bib0060) 2010; 59 Maestre (10.1016/j.jprocont.2018.06.004_bib0085) 2014 10.1016/j.jprocont.2018.06.004_bib0125 Ionescu (10.1016/j.jprocont.2018.06.004_bib0160) 2016 Maxim (10.1016/j.jprocont.2018.06.004_bib0185) 2017 Alessio (10.1016/j.jprocont.2018.06.004_bib0030) 2007 Farina (10.1016/j.jprocont.2018.06.004_bib0065) 2016; 89 Samad (10.1016/j.jprocont.2018.06.004_bib0010) 2017; 37 Muros (10.1016/j.jprocont.2018.06.004_bib0075) 2016 De Keyser (10.1016/j.jprocont.2018.06.004_bib0095) 1981; 17 Folea (10.1016/j.jprocont.2018.06.004_bib0130) 2016; 12 Davison (10.1016/j.jprocont.2018.06.004_bib0020) 2010 Dutta (10.1016/j.jprocont.2018.06.004_bib0175) 2014 Stewart (10.1016/j.jprocont.2018.06.004_bib0060) 2010; 59 Dutta (10.1016/j.jprocont.2018.06.004_bib0110) 2014; 22 De Keyser (10.1016/j.jprocont.2018.06.004_bib0140) 2003 Hermans (10.1016/j.jprocont.2018.06.004_bib0045) 2012; 85 Bodenburg (10.1016/j.jprocont.2018.06.004_bib0070) 2016 Conte (10.1016/j.jprocont.2018.06.004_bib0050) 2016; 69 Maciejowski (10.1016/j.jprocont.2018.06.004_bib0170) 2000 Bauer (10.1016/j.jprocont.2018.06.004_bib0005) 2016; 38 Negenborn (10.1016/j.jprocont.2018.06.004_bib0090) 2014; 34 De Keyser (10.1016/j.jprocont.2018.06.004_bib0105) 2003 Camacho (10.1016/j.jprocont.2018.06.004_bib0150) 1999 Wang (10.1016/j.jprocont.2018.06.004_bib0145) 2009 Ionescu (10.1016/j.jprocont.2018.06.004_bib0115) 2014; 28 Pop (10.1016/j.jprocont.2018.06.004_bib0165) 2012; 6 Christofides (10.1016/j.jprocont.2018.06.004_bib0035) 2013; 51 Kalsi (10.1016/j.jprocont.2018.06.004_bib0025) 2009; 82 Soltesz (10.1016/j.jprocont.2018.06.004_bib0155) 2016; 27 Engell (10.1016/j.jprocont.2018.06.004_bib0180) 2007; 17 Samad (10.1016/j.jprocont.2018.06.004_bib0015) 2007; 17 Quijano (10.1016/j.jprocont.2018.06.004_bib0080) 2017; 37 De Keyser (10.1016/j.jprocont.2018.06.004_bib0100) 1988; 24 Dutta (10.1016/j.jprocont.2018.06.004_bib0135) 2015; 36 Farina (10.1016/j.jprocont.2018.06.004_bib0055) 2012; 48 Scattolini (10.1016/j.jprocont.2018.06.004_bib0040) 2009; 19 Ltdc:Gá:rtdclvez-Carrillo (10.1016/j.jprocont.2018.06.004_bib0120) 2009; 83 |
| References_xml | – volume: 28 start-page: 537 year: 2014 end-page: 546 ident: bib0115 article-title: Lessons learned from closed loops in engineering: towards a multivariable approach regulating depth of anaesthesia publication-title: J. Clin. Monit. Comput. – volume: 17 start-page: 167 year: 1981 end-page: 174 ident: bib0095 article-title: A self-tuning multistep predictor application publication-title: Automatica – volume: 85 start-page: 1162 year: 2012 end-page: 1177 ident: bib0045 article-title: Assessment of non-centralised model predictive control techniques for electrical power networks publication-title: Int. J. Control – reference: R. De Keyser, J. Donald III, Z. Lu, H. De Waard, MPC in semiconductor processing, MPC in thermal processing, USA Patents (08/597-438, 6207936,6373033). – volume: 89 start-page: 192 year: 2016 end-page: 203 ident: bib0065 article-title: Assessment and comparison of distributed model predictive control schemes: application to a natural gas refrigeration plant publication-title: Comput. Chem. Eng. – year: 1999 ident: bib0150 article-title: Model Predictive Control – volume: 48 start-page: 1088 year: 2012 end-page: 1096 ident: bib0055 article-title: Distributed predictive control: a non-cooperative algorithm with neighbor-to-neighbor communication for linear systems publication-title: Automatica – year: 2000 ident: bib0170 article-title: Predictive Control with Constraints – volume: 69 start-page: 117 year: 2016 end-page: 125 ident: bib0050 article-title: Distributed synthesis and stability of cooperative distributed model predictive control for linear systems publication-title: Automatica – volume: 37 start-page: 70 year: 2017 end-page: 97 ident: bib0080 article-title: The role of population games and evolutionary dynamics in distributed control systems publication-title: IEEE Control Syst. – volume: 6 start-page: 453 year: 2012 end-page: 461 ident: bib0165 article-title: Robustness evaluation of fractional order control for varying time delay processes publication-title: Signal Image Video Process. – volume: 83 start-page: 743 year: 2009 end-page: 752 ident: bib0120 article-title: Nonlinear predictive control with dead-time compensator: application to a solar power plant publication-title: Solar Energy – volume: 59 start-page: 460 year: 2010 end-page: 469 ident: bib0060 article-title: Cooperative distributed model predictive control publication-title: Syst. Control Lett. – volume: 37 start-page: 17 year: 2017 end-page: 18 ident: bib0010 article-title: A survey on industry impact and challenges thereof [technical activities] publication-title: IEEE Control Syst. – year: 2009 ident: bib0145 article-title: Control System Design and Implementation Using MATLAB – volume: 38 start-page: 1 year: 2016 end-page: 10 ident: bib0005 article-title: The current state of control loop performance monitoring – a survey of application in industry publication-title: J. Process Control – volume: 22 start-page: 114 year: 2014 end-page: 124 ident: bib0110 article-title: Comparison of two-level NMPC and ILC strategies for wet-clutch control publication-title: Control Eng. Pract. – year: 2014 ident: bib0085 article-title: Distributed Model Predictive Control Made Easy – year: 2003 ident: bib0140 article-title: The disturbance model in model based predictive control publication-title: Proc. of the IEEE Conference on Control Applications (CCA 2003) – volume: 82 start-page: 541 year: 2009 end-page: 554 ident: bib0025 article-title: On decentralised control of non-linear interconnected systems publication-title: Int. J. Control – year: 2017 ident: bib0185 article-title: A methodology for control structure adaptation in presence of varying, unknown sub-system interaction degree publication-title: Proc. of the 22nd IEEE International Conference on Emerging Technologies in Factory Automation ETFA – volume: 24 start-page: 149 year: 1988 end-page: 163 ident: bib0100 article-title: A comparative study of self-adaptive long-range predictive control methods publication-title: Automatica – volume: 12 start-page: 736 year: 2016 end-page: 744 ident: bib0130 article-title: A portable implementation on industrial devices of a predictive controller using graphical programming publication-title: IEEE Trans. Ind. Inf. – start-page: 249 year: 2016 end-page: 256 ident: bib0070 article-title: Cooperative reconfiguration of locally interconnected systems with limited model information: a plug-and-play approach publication-title: Proc. of the 2016 European Control Conference – volume: 36 start-page: 369 year: 2015 end-page: 380 ident: bib0135 article-title: A pragmatic approach to distributed nonlinear model predictive control: application to a hydrostatic drive train publication-title: Optim. Control Appl. Methods – start-page: 6695 year: 2014 end-page: 6700 ident: bib0175 article-title: Certification of a class of industrial predictive controllers without terminal conditions publication-title: Proc. of the 53rd IEEE Conference on Decision and Control – year: 2003 ident: bib0105 article-title: Model based predictive control for linear systems publication-title: UNESCO Encyclopaedia of Life Support Systems, Control Systems, Robotics and Automation, vol. XI, Article contribution 6.43.16.1 – volume: 17 start-page: 203 year: 2007 end-page: 219 ident: bib0180 article-title: Feedback control for optimal process operation publication-title: J. Process Control – volume: 51 start-page: 21 year: 2013 end-page: 41 ident: bib0035 article-title: Distributed model predictive control: a tutorial review and future research directions publication-title: Comput. Chem. Eng. – volume: 34 start-page: 84 year: 2014 end-page: 97 ident: bib0090 article-title: Distributed model predictive control. An overview and roadmap of future research opportunities publication-title: IEEE Control Syst. Mag. – volume: 17 start-page: 191 year: 2007 end-page: 201 ident: bib0015 article-title: System architecture for process automation: review and trends publication-title: J. Process Control – start-page: 1103 year: 2016 end-page: 1108 ident: bib0160 article-title: Constrained multivariable predictive control of a train of cryogenic c-13 separation columns publication-title: Proc. of the 11th IFAC Symposium on Dynamics and Control of Process Systems including Biosystems – start-page: 190 year: 2016 end-page: 195 ident: bib0075 article-title: Cooperative game theory tools to detect critical nodes in distributed control systems publication-title: Proc. of the 2016 European Control Conference – year: 2010 ident: bib0020 article-title: Decentralized Control of Large-Scale systems – start-page: 2813 year: 2007 end-page: 2818 ident: bib0030 article-title: Decentralised model predictive control of constrained linear systems publication-title: Proc. of the European Control Conference – volume: 27 start-page: 1857 year: 2016 end-page: 1873 ident: bib0155 article-title: An automatic tuner with short experiment and probabilistic parameterization publication-title: Int. J. Robust Nonlinear Control – volume: 19 start-page: 723 year: 2009 end-page: 731 ident: bib0040 article-title: Architectures for distributed and hierarchical model predictive control− a review publication-title: J. Process Control – volume: 69 start-page: 117 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0050 article-title: Distributed synthesis and stability of cooperative distributed model predictive control for linear systems publication-title: Automatica doi: 10.1016/j.automatica.2016.02.009 – volume: 51 start-page: 21 year: 2013 ident: 10.1016/j.jprocont.2018.06.004_bib0035 article-title: Distributed model predictive control: a tutorial review and future research directions publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2012.05.011 – volume: 22 start-page: 114 year: 2014 ident: 10.1016/j.jprocont.2018.06.004_bib0110 article-title: Comparison of two-level NMPC and ILC strategies for wet-clutch control publication-title: Control Eng. Pract. doi: 10.1016/j.conengprac.2013.10.003 – volume: 59 start-page: 460 issue: 8 year: 2010 ident: 10.1016/j.jprocont.2018.06.004_bib0060 article-title: Cooperative distributed model predictive control publication-title: Syst. Control Lett. doi: 10.1016/j.sysconle.2010.06.005 – volume: 85 start-page: 1162 issue: 8 year: 2012 ident: 10.1016/j.jprocont.2018.06.004_bib0045 article-title: Assessment of non-centralised model predictive control techniques for electrical power networks publication-title: Int. J. Control doi: 10.1080/00207179.2012.679972 – volume: 36 start-page: 369 issue: 3 year: 2015 ident: 10.1016/j.jprocont.2018.06.004_bib0135 article-title: A pragmatic approach to distributed nonlinear model predictive control: application to a hydrostatic drive train publication-title: Optim. Control Appl. Methods doi: 10.1002/oca.2141 – volume: 6 start-page: 453 issue: 3 year: 2012 ident: 10.1016/j.jprocont.2018.06.004_bib0165 article-title: Robustness evaluation of fractional order control for varying time delay processes publication-title: Signal Image Video Process. doi: 10.1007/s11760-012-0322-4 – year: 2017 ident: 10.1016/j.jprocont.2018.06.004_bib0185 article-title: A methodology for control structure adaptation in presence of varying, unknown sub-system interaction degree – volume: 27 start-page: 1857 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0155 article-title: An automatic tuner with short experiment and probabilistic parameterization publication-title: Int. J. Robust Nonlinear Control doi: 10.1002/rnc.3640 – volume: 82 start-page: 541 issue: 3 year: 2009 ident: 10.1016/j.jprocont.2018.06.004_bib0025 article-title: On decentralised control of non-linear interconnected systems publication-title: Int. J. Control doi: 10.1080/00207170802187247 – volume: 19 start-page: 723 issue: 5 year: 2009 ident: 10.1016/j.jprocont.2018.06.004_bib0040 article-title: Architectures for distributed and hierarchical model predictive control− a review publication-title: J. Process Control doi: 10.1016/j.jprocont.2009.02.003 – volume: 37 start-page: 70 issue: 1 year: 2017 ident: 10.1016/j.jprocont.2018.06.004_bib0080 article-title: The role of population games and evolutionary dynamics in distributed control systems publication-title: IEEE Control Syst. doi: 10.1109/MCS.2016.2621479 – ident: 10.1016/j.jprocont.2018.06.004_bib0125 – volume: 28 start-page: 537 year: 2014 ident: 10.1016/j.jprocont.2018.06.004_bib0115 article-title: Lessons learned from closed loops in engineering: towards a multivariable approach regulating depth of anaesthesia publication-title: J. Clin. Monit. Comput. doi: 10.1007/s10877-013-9535-5 – year: 2014 ident: 10.1016/j.jprocont.2018.06.004_bib0085 – start-page: 2813 year: 2007 ident: 10.1016/j.jprocont.2018.06.004_bib0030 article-title: Decentralised model predictive control of constrained linear systems – year: 2003 ident: 10.1016/j.jprocont.2018.06.004_bib0105 article-title: Model based predictive control for linear systems – volume: 17 start-page: 167 issue: 1 year: 1981 ident: 10.1016/j.jprocont.2018.06.004_bib0095 article-title: A self-tuning multistep predictor application publication-title: Automatica doi: 10.1016/0005-1098(81)90092-3 – volume: 48 start-page: 1088 issue: 6 year: 2012 ident: 10.1016/j.jprocont.2018.06.004_bib0055 article-title: Distributed predictive control: a non-cooperative algorithm with neighbor-to-neighbor communication for linear systems publication-title: Automatica doi: 10.1016/j.automatica.2012.03.020 – volume: 89 start-page: 192 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0065 article-title: Assessment and comparison of distributed model predictive control schemes: application to a natural gas refrigeration plant publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2016.03.001 – volume: 83 start-page: 743 year: 2009 ident: 10.1016/j.jprocont.2018.06.004_bib0120 article-title: Nonlinear predictive control with dead-time compensator: application to a solar power plant publication-title: Solar Energy doi: 10.1016/j.solener.2008.11.005 – start-page: 6695 year: 2014 ident: 10.1016/j.jprocont.2018.06.004_bib0175 article-title: Certification of a class of industrial predictive controllers without terminal conditions – volume: 34 start-page: 84 issue: 4 year: 2014 ident: 10.1016/j.jprocont.2018.06.004_bib0090 article-title: Distributed model predictive control. An overview and roadmap of future research opportunities publication-title: IEEE Control Syst. Mag. – year: 2000 ident: 10.1016/j.jprocont.2018.06.004_bib0170 – year: 2003 ident: 10.1016/j.jprocont.2018.06.004_bib0140 article-title: The disturbance model in model based predictive control – start-page: 190 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0075 article-title: Cooperative game theory tools to detect critical nodes in distributed control systems – year: 2010 ident: 10.1016/j.jprocont.2018.06.004_bib0020 – year: 1999 ident: 10.1016/j.jprocont.2018.06.004_bib0150 – volume: 37 start-page: 17 issue: 1 year: 2017 ident: 10.1016/j.jprocont.2018.06.004_bib0010 article-title: A survey on industry impact and challenges thereof [technical activities] publication-title: IEEE Control Syst. doi: 10.1109/MCS.2016.2621438 – volume: 24 start-page: 149 issue: 2 year: 1988 ident: 10.1016/j.jprocont.2018.06.004_bib0100 article-title: A comparative study of self-adaptive long-range predictive control methods publication-title: Automatica doi: 10.1016/0005-1098(88)90024-6 – start-page: 1103 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0160 article-title: Constrained multivariable predictive control of a train of cryogenic c-13 separation columns – volume: 17 start-page: 191 issue: 3 year: 2007 ident: 10.1016/j.jprocont.2018.06.004_bib0015 article-title: System architecture for process automation: review and trends publication-title: J. Process Control doi: 10.1016/j.jprocont.2006.10.010 – volume: 17 start-page: 203 year: 2007 ident: 10.1016/j.jprocont.2018.06.004_bib0180 article-title: Feedback control for optimal process operation publication-title: J. Process Control doi: 10.1016/j.jprocont.2006.10.011 – volume: 38 start-page: 1 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0005 article-title: The current state of control loop performance monitoring – a survey of application in industry publication-title: J. Process Control doi: 10.1016/j.jprocont.2015.11.002 – start-page: 249 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0070 article-title: Cooperative reconfiguration of locally interconnected systems with limited model information: a plug-and-play approach – volume: 12 start-page: 736 year: 2016 ident: 10.1016/j.jprocont.2018.06.004_bib0130 article-title: A portable implementation on industrial devices of a predictive controller using graphical programming publication-title: IEEE Trans. Ind. Inf. doi: 10.1109/TII.2016.2532118 – year: 2009 ident: 10.1016/j.jprocont.2018.06.004_bib0145 |
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