Details

Title

Offset-free nonlinear Model Predictive Control with state-space process models

Journal title

Archives of Control Sciences

Yearbook

2017

Issue

No 4

Authors

Divisions of PAS

Nauki Techniczne

Publisher

Committee of Automatic Control and Robotics PAS

Date

2017

Identifier

DOI: 10.1515/acsc-2017-0035 ; ISSN 1230-2384

Source

Archives of Control Sciences; 2017; No 4

References

Pannocchiaand (2003), Disturbance models for offset - free model predictive control, AIChE J, 15, 426. ; Qinand (2003), survey of industrial model predictive control technology, Control Engineering Practice, 16, 733. ; Raoand (1999), Steady states and constraints in model predictive control, AIChE J, 17, 1266. ; Morariand (2012), Nonlinear offset - free model predictive control, Automatica, 12, 2059. ; Tatjewski (2014), Offset - free nonlinear predictive control with measured state and unknown asymptotically constant disturbances In Aktualne problemy automatyki i robotyki ( Actual problems in automation and robotics pages Academic Publisher EXIT, null, 24, 288. ; Blevins (2003), Control Unleashed The Research Triangle, Advanced Society. ; Tatjewski (2008), Advanced control and on - line process optimization in multilayer structures in, Annual Reviews Control, 21, 71. ; Rossiter (2003), Model Based Predictive Control London New York, null, 19. ; Astromand (1997), Controlled Systems Upper Saddle, Computer, 1. ; Maederand (2010), Offset - free reference tracking with model predictive control, Automatica, 11, 1469. ; Muskeand (2002), Disturbance modeling for offset - free linear model predictive control of Process Control, null, 13, 617. ; Camachoand (1999), Model Predictive Control Verlag, null. ; Rawlingsand (2009), Model Predictive Control Theory Nob Publishing, Design, 18. ; Tatjewski (2014), Disturbance modeling and state estimation for offset - free predictive control with state - spaced process models of and, Int Journal Applied Mathematics Computer Science, 23, 313. ; BirkandM (1988), Extended Luenberger observer for non - linear multivariable systems of Control, Int J, 47, 1823. ; Maciejowski (2002), Predictive Control, null. ; Tatjewski (2016), zaawansowane procesów przemysłowych Advanced Control of Industrial Processes Second revised edition book in Polish Academic Publisher EXIT Warszawa, null, 25. ; Tatjewski (2007), Advanced Control of Industrial Processes Verlag, null, 20. ; Tatjewski (2017), Offset - free nonlinear model predictive control In Trends in Advanced Intelligent Control Optimization and Automation of th Polish Control Conference in Intelligent pages, Proc Advances Systems Computing, 26, 577. ; Ławryńczuk (2014), Computationally Efficient Model Predictive Control Neural Network Approach Studies in Systems Decision and Control Verlag, Algorithms. ; Tatjewski (2010), Supervisory predictive control and on - line set - point optimization of and, Int J Applied Mathematics Computer Science, 22, 483. ; Wang (2009), Model Predictive Control System Design and Implementation using Verlag, null, 28. ; Pannocchiaand (2007), Combined design of disturbance model and observer for offset - free model predictive control on Automatic Control, IEEE Trans, 14, 1048. ; Blevins (2013), Control Foundation The Research Triangle, Advanced Society. ; Gonzalez (2008), Conditions for offset elimination in state space receding horizon controllers tutorial analysis and Processing, Chemical Engineering, 2184. ; Tatjewskiand (2006), in model - based predictive control of and, Soft computing Int J Applied Mathematics Computer Science, 27, 7.
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