Min-max feedback model predictive control for constrained linear systems
Abstract
Min-max feedback formulations of model predictive control are discussed, both in the fixed and variable horizon contexts. The control schemes the authors discuss introduce, in the control optimization, the notion that feedback is present in the receding-horizon implementation of the control. This leads to improved performance, compared to standard model predictive control, and resolves the feasibility difficulties that arise with the min-max techniques that are documented in the literature. The stabilizing properties of the methods are discussed as well as some practical implementation details.
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Other robust MPC schemes including min-max optimization and sliding mode techniques improve robustness without significant increase of complexities.
“Other robust MPC schemes, including min-max optimization [25], [26] and sliding mode techniques [27], [28], are also employed to improve robustness without significant increase of complexities.”
From Incremental Model Predictive Control Exploiting Time-Delay Estimation for a Robot Manipulator (2022) · cites this paper as [25]
Cites
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Constrained model predictive control: Stability and optimality
Mayne, D. Q., Rawlings, J. B., Rao, C. V., & Scokaert, P. O. M. (2000) · Automatica · doi:10.1016/s0005-1098(99)00214-9 · Cited by 8,736 · see citing works
Self-citationMarruedo, D. L., Alamo, T., & Camacho, E. F. (2004) · Proceedings of the 41st IEEE Conference on Decision and Control, 2002. · doi:10.1109/cdc.2002.1185106 · Cited by 340 · see citing works
Rubagotti, M., Raimondo, D. M., Ferrara, A., & Magni, L. (2011) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2010.2074590 · Cited by 196 · see citing works
Disturbance Compensating Model Predictive Control With Application to Ship Heading Control
Li, Z., & Sun, J. (2011) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2011.2106212 · Cited by 168 · see citing works
Incremental Model Predictive Control Exploiting Time-Delay Estimation for a Robot Manipulator
Wang, Y., Leibold, M., Lee, J., Ye, W., Xie, J., & Buss, M. (2022) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2022.3142629 · Cited by 52 · see citing works
- Authors
- Scokaert, P. O. M., & Mayne, D. Q.
- Affiliations
- University of Wisconsin–Madison (US)
- Imperial College London (GB)
- Venue
- IEEE Transactions on Automatic Control
- Published
- 1998
- Volume
- 43
- Issue
- 8
- Pages
- 1136-1142
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2164957979
- Cited by
- 929
- References
- 7
- Citations by year
- 2026: 27 · 2025: 28 · 2024: 30 · 2023: 34 · 2022: 37 · 2021: 46 · 2020: 45 · 2019: 43 · 2018: 37 · 2017: 26 · 2016: 33 · 2015: 52 · 2014: 36 · 2013: 39 · 2012: 35
- FWCI
- 23.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Automatic Control (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Keywords
- min-max model predictive control, constrained linear systems, model predictive control, feasibility, stability analysis, robust control
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