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Zakeri Y, Sheikholeslam F, Haeri M. A Unified Approach to Structural Analysis and Design of Model Predictive Controllers. jocee 2022; 1 (1) :1-9
URL: http://jocee.kntu.ac.ir/article-1-25-en.html
1- Isfahan University of Technology
2- Sharif University of Technology
Abstract:   (1193 Views)
Designing linear MPC with pre-specified closed-loop characteristics for stability and robustness consideration as well as optimal time domain performance, is an interesting issue. In this paper, we develop a new enabling formulation, which can explicitly show existence and properties of the linear controller counterpart for transfer function-based MPC, known as Generalized Predictive Control. This development allows one to transform desired closed loop specifications to constraints on new-defined variables of the GPC optimization problem along with desired time domain performance-related design parameters. Input output constraints also can be transformed to constraints on these new variables. Fantastic results are illustrated by an ongoing example. It is a unified approach to answer some key questions in both theory and application such as analysis and design for desired performance, stability and robustness, controller matching, reference governor GPC, and design of model reference predictive control in data-driven control.
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Type of Article: Research paper | Subject: General
Received: 2021/07/18 | Accepted: 2022/02/19 | ePublished ahead of print: 2022/04/26 | Published: 2022/07/1

1. [1] S. D. Cairano and A. Bemporad, "Model Predic-tive Control Tuning by Controller Matching," IEEE Transactions on Automatic Control, vol. 55, no. NO. 1, pp. 185-190, 2010. [DOI:10.1109/TAC.2009.2033838]
2. [2] E. F. Camacho and C. Bordons, Model Predic-tive Control, Springer, 1999. [DOI:10.1007/978-1-4471-3398-8]
3. [3] A. S. Yamashita, A. C. Zanin and D. Odloak, "Tuning of model Predictive Control with Multi-Objective Optimization," Brazilian Journal of Chemi-cal Engineering, vol. 33, no. 02, pp. 333-346, 2016. [DOI:10.1590/0104-6632.20160332s20140212]
4. [4] P. Bagheri and A. Khaki Sedigh, "Review of Model Predictive Control Tuning Methods and Modern Tuning Solutions," Journal of Control (Persian Edi-tion), vol. 8, no. 3, pp. 69-85, 2014.
5. [5] J. L. Garriga and M. Soroush, "Model Predic-tive Control Tuning Methods: A Review," Ind. Eng. Chem. Res., p. 3505-3515, 2010. [DOI:10.1021/ie900323c]
6. [6] M. Alhajeri and M. Soroush, "Tuning Guide-lines for Model-Predictive Control," Ind. Eng. Chem. Res., p. 4177-4191, 2020. [DOI:10.1021/acs.iecr.9b05931]
7. [7] C. Mohtadi and D. W. Clarke, "Generalized Predictive Control, LQ, or Pole-placement: A unified approach.," in 25th Conference on Decision and Con-trol, Athens, Greece, 1986. [DOI:10.1109/CDC.1986.267142]
8. [8] I. D. Landau, M. M'Saad and A. Karimi, Adap-tive Control, Algorithms, Analysis and Applications, Springer-Verlag London Limited, 2011.
9. [9] K. Lim, W. Ho, T. Lee, K. Ling and w. xu, "Generalized predictive controller with pole re-striction," IEE Proc.-Control Theory Appl., vol. 145, pp. 219-225, March 1998. [DOI:10.1049/ip-cta:19981740]
10. [10] E. N. Hartley and J. M. Maciejowski, "De-signing Output-Feedback Predictive Controllers by Reverse-Engineering Existing LTI Controllers," IEEE Transaction on Automatic Control, vol. 58, no. 11, pp. 2034-2939, 2013. [DOI:10.1109/TAC.2013.2258781]
11. [11] Q. N. Tran, L. O¨ zkan and A. A.C.P.M. Backx, "Generalized Predictive Control tuning by con-troller matching," Journal of Process Control, vol. 25, pp. 4889-4894, 2015. [DOI:10.1016/j.jprocont.2014.10.002]
12. [12] G. Shah and S. Engell, "Tuning MPC for De-sired Closed-Loop Performance for SISO Systems," in 18th Mediterranean Conference on Control & Automa-tion, Morroco, 2010. [DOI:10.1109/MED.2010.5547799]
13. [13] E. Garone, S. Di Cairano and I. Kolm, "Ref-erence and command governors for systems with con-straints: A survey on theory and applications," Auto-matica, pp. 306-328, 2017. [DOI:10.1016/j.automatica.2016.08.013]
14. [14] M. M. Nicotra and E. Garone, "The Explicit Reference Governor, A General Framework for the Closed-Form Control," IEEE Control Systems Maga-zine, pp. 89-107, 2018. [DOI:10.1109/MCS.2018.2830081]
15. [15] I. Landau, "Robust R-S-T Digital Control," in IEEE, Advanced Process Control Workshop, Vancou-ver, 2002.
16. [16] O. Sename, "Pole placement control: state space and polynomial approaches," 2017. [Online]. Available: www.gipsa-lab.fr/~o.sename.
17. [17] G. Shah, S. Engel, "Tuning MPC for Desired Closed-Loop Performance for SISO Systems," Moroc-co, 2010. [DOI:10.1109/MED.2010.5547799]
18. [18] J. Maciejowski, "Reverse- Engineering Existing Controllers for MPC Design," 2007. [DOI:10.3182/20071017-3-BR-2923.00069]

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