TR2016-043
Indirect Adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty
-
- "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.
-
MERL Contact:
-
Research Area:
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.
Related News & Events
-
NEWS Stefano Di Cairano appointed Vice-Chair of IFAC Technical Committee for Optimal Control Date: October 18, 2017
Where: International Federation of Automatic Control
MERL Contact: Stefano Di Cairano
Research Area: ControlBrief- MERL Mechatronics Senior Principal Research Scientist and Senior Optimization-based Control Team Leader, Stefano Di Cairano, was recently appointed the Vice-Chair of IFAC (International Federation of Automatic Control) Technical Committee for Optimal Control. His term will continue through July 2020.
-
NEWS MERL makes a strong showing at the American Control Conference Date: July 6, 2016 - July 8, 2016
Where: American Control Conference (ACC)
MERL Contacts: Scott A. Bortoff; Petros T. Boufounos; Stefano Di Cairano; Abraham Goldsmith; Christopher R. Laughman; Daniel N. Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, Machine LearningBrief- The premier American Control Conference (ACC) takes place in Boston July 6-8. This year MERL researchers will present a record 20 papers(!) at ACC, with several contributions, especially in autonomous vehicle path planning and in Model Predictive Control (MPC) theory and applications, including manufacturing machines, electric motors, satellite station keeping, and HVAC. Other important themes developed in MERL's presentations concern adaptation, learning, and optimization in control systems.