TR2016-043

Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty


    •  Di Cairano, S., "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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      • @inproceedings{DiCairano2016jul2,
      • author = {{Di Cairano}, S.},
      • 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 = {http://www.merl.com/publications/TR2016-043}
      • }
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    Mechatronics


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.