TR2016-043
Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty
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- , "Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty", American Control Conference (ACC), DOI: 10.1109/ACC.2016.7525467, July 2016, pp. 3570-3575.BibTeX TR2016-043 PDF
- @inproceedings{DiCairano2016jul2,
- author = {Di Cairano, Stefano},
- title = {Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty},
- booktitle = {American Control Conference (ACC)},
- year = 2016,
- pages = {3570--3575},
- month = jul,
- doi = {10.1109/ACC.2016.7525467},
- url = {https://www.merl.com/publications/TR2016-043}
- }
- , "Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty", American Control Conference (ACC), DOI: 10.1109/ACC.2016.7525467, July 2016, pp. 3570-3575.
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Abstract:
We develop an indirect adaptive model predictive control algorithm for uncertain linear systems subject to constraints. The system is modeled as a polytopic linear parameter varying system where the convex combination vector is constant but unknown. The terminal cost and set are constructed from a parameter-dependent Lyapunov function and the associated control law, and robust control invariant set constraints are enforced. The proposed design ensures robust constraint satisfaction and recursive feasibility, is input-to-state stable with respect to the parameter estimation error and it only requires the online solution of quadratic programs.
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