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Reference governor for constrained nonlinear systems
Abstract
This paper addresses the problem of satisfying pointwise-in-time input and/or state hard constraints in nonlinear control systems. The approach is based on conceptual tools of predictive control and consists of adding to a primal compensated nonlinear system a reference governor. This is a discrete-time device which online handles the reference to be tracked, taking into account the current value of the state in order to satisfy the prescribed constraints. The resulting hybrid system is proved to fulfil the constraints as well as stability and tracking requirements.
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Citations
Cited by
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
Model predictive control: past, present and future
Morari, M., & H. Lee, J. (1999) · Computers & Chemical Engineering · doi:10.1016/s0098-1354(98)00301-9 · Cited by 2,335
Reference and command governors for systems with constraints: A survey on theory and applications
Garone, E., Di Cairano, S., & Kolmanovsky, I. (2017) · Automatica · doi:10.1016/j.automatica.2016.08.013 · Cited by 466
Gilbert, E., & Kolmanovsky, I. (2002) · Automatica · doi:10.1016/s0005-1098(02)00135-8 · Cited by 403
Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay
Li, D.-P., Liu, Y.-J., Tong, S., Chen, C. L. P., & Li, D.-J. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2799683 · Cited by 382
Metadata
- Authors
- Bemporad, A.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 1998-03
- Volume
- 43
- Issue
- 3
- Pages
- 415-419
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2151301943
- Cited by
- 552
- References
- 0
- FWCI
- 7.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bemporad, A. (1998). Reference governor for constrained nonlinear systems. IEEE Transactions on Automatic Control. https://doi.org/10.1109/9.661611
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
