The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Robust model predictive control of constrained linear systems with bounded disturbances
Abstract
This paper provides a novel solution to the problem of robust model predictive control of constrained, linear, discrete-time systems in the presence of bounded disturbances. The optimal control problem that is solved online includes, uniquely, the initial state of the model employed in the problem as a decision variable. The associated value function is zero in a disturbance invariant set that serves as the 'origin' when bounded disturbances are present, and permits a strong stability result, namely robust exponential stability of the disturbance invariant set for the controlled system with bounded disturbances, to be obtained. The resultant online algorithm is a quadratic program of similar complexity to that required in conventional model predictive control.
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Citations
Cites
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
Self-citation
Cited by
Optimization over state feedback policies for robust control with constraints
Goulart, P. J., Kerrigan, E. C., & Maciejowski, J. M. (2006) · Automatica · doi:10.1016/j.automatica.2005.08.023 · Cited by 580
Tube‐based robust nonlinear model predictive control
Mayne, D. Q., Kerrigan, E. C., van Wyk, E. J., & Falugi, P. (2011) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.1758 · Cited by 462
Self-citationLearning deep control policies for autonomous aerial vehicles with MPC-guided policy search
Zhang, T., Kahn, G., Levine, S., & Abbeel, P. (2016) · 2016 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2016.7487175 · Cited by 452
“Model predictive control (MPC) is an effective and reliable method for controlling robotic systems, particularly autonomous aerial vehicles such as quadcopters, because of its robustness to moderate model errors [26], ability to use high-level objectives [41], and relative simplicity.”
MethodModel Predictive Control approach for guidance of spacecraft rendezvous and proximity maneuvering
Di Cairano, S., Park, H., & Kolmanovsky, I. (2012) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.2827 · Cited by 273
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
Metadata
- Authors
- Mayne, D. Q., Seron, M. M., & Raković, S. V.
- Venue
- Automatica
- Publisher
- Elsevier BV
- Published
- 2005-02
- Volume
- 41
- Issue
- 2
- Pages
- 219-224
- ISSN
- 0005-1098 (ISSN-L)
- OpenAlex
- W1981723834
- Cited by
- 1,672
- References
- 1
- FWCI
- 31.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
