TR2022-061
Reference Governor for Hybrid Dynamical Systems
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- "Reference Governor for Hybrid Dynamical Systems", American Control Conference (ACC), DOI: 10.23919/ACC53348.2022.9867303, June 2022.BibTeX TR2022-061 PDF
- @inproceedings{Sanfelice2022jun,
- author = {Sanfelice, Ricardo G. and Di Cairano, Stefano},
- title = {Reference Governor for Hybrid Dynamical Systems},
- booktitle = {American Control Conference (ACC)},
- year = 2022,
- month = jun,
- doi = {10.23919/ACC53348.2022.9867303},
- url = {https://www.merl.com/publications/TR2022-061}
- }
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- "Reference Governor for Hybrid Dynamical Systems", American Control Conference (ACC), DOI: 10.23919/ACC53348.2022.9867303, June 2022.
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Research Areas:
Abstract:
We formulate a reference governor algorithm for hybrid systems modeled as hybrid equations, in which the continuous dynamics are governed by a constrained differential equation and the discrete dynamics by a constrained difference equation. Basic definitions, models, and properties of the proposed hybrid reference governor approach are introduced and a time-based implementation is formulated. We apply the methodology to hybrid equations with linear right-hand side in both the differential and difference equations and with explicit logic variables. We illustrate the approach in examples
Related News & Events
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NEWS MERL researchers presented 9 papers at the American Control Conference (ACC) Date: June 8, 2022 - June 10, 2022
Where: Atlanta, GA
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference in Atlanta, GA, MERL presented 9 papers on subjects including autonomous-vehicle decision making and motion planning, realtime Bayesian inference and learning, reference governors for hybrid systems, Bayesian optimization, and nonlinear control.