Robust Stability of Barrier-Based Model Predictive Control

Panagiotis Petsagkourakis; William P. Heath; Joaquin Carrasco; Constantinos Theodoropoulos

doi:10.1109/tac.2020.3010770

Robust Stability of Barrier-Based Model Predictive Control

Panagiotis Petsagkourakis
, William P. Heath
, Joaquin Carrasco
, Constantinos Theodoropoulos

University of Manchester

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

Crynodeb

Conditions for robust input-output stability of barrier-based model predictive control of linear systems with linear and convex nonlinear (hard or soft) constraints are established through the construction of integral quadratic constraints (IQCs). The IQCs can be used to determine sufficient conditions for global closed-loop stability. In particular, conditions for robust stability can be obtained in the presence of unstructured model uncertainty. IQCs with both static and dynamic multipliers are developed and appropriate convex searches for the multipliers are presented. The effectiveness of the robust stability analysis is demonstrated through an illustrative numerical example

Iaith wreiddiol	Anadnabyddus
Tudalennau (o-i)	1879-1886
Nifer y tudalennau	8
Cyfnodolyn	IEEE Transactions on Automatic Control
Cyfrol	66
Rhif cyhoeddi	4
Dyddiad ar-lein cynnar	21 Gorff 2020
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/tac.2020.3010770
Statws	Cyhoeddwyd - 1 Ebr 2021
Cyhoeddwyd yn allanol	Ie

Mynediad at Ddogfen

10.1109/tac.2020.3010770

Dyfynnu hyn

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abstract = "Conditions for robust input-output stability of barrier-based model predictive control of linear systems with linear and convex nonlinear (hard or soft) constraints are established through the construction of integral quadratic constraints (IQCs). The IQCs can be used to determine sufficient conditions for global closed-loop stability. In particular, conditions for robust stability can be obtained in the presence of unstructured model uncertainty. IQCs with both static and dynamic multipliers are developed and appropriate convex searches for the multipliers are presented. The effectiveness of the robust stability analysis is demonstrated through an illustrative numerical example",

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AU - Carrasco, Joaquin

AU - Theodoropoulos, Constantinos

PY - 2021/4/1

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N2 - Conditions for robust input-output stability of barrier-based model predictive control of linear systems with linear and convex nonlinear (hard or soft) constraints are established through the construction of integral quadratic constraints (IQCs). The IQCs can be used to determine sufficient conditions for global closed-loop stability. In particular, conditions for robust stability can be obtained in the presence of unstructured model uncertainty. IQCs with both static and dynamic multipliers are developed and appropriate convex searches for the multipliers are presented. The effectiveness of the robust stability analysis is demonstrated through an illustrative numerical example

AB - Conditions for robust input-output stability of barrier-based model predictive control of linear systems with linear and convex nonlinear (hard or soft) constraints are established through the construction of integral quadratic constraints (IQCs). The IQCs can be used to determine sufficient conditions for global closed-loop stability. In particular, conditions for robust stability can be obtained in the presence of unstructured model uncertainty. IQCs with both static and dynamic multipliers are developed and appropriate convex searches for the multipliers are presented. The effectiveness of the robust stability analysis is demonstrated through an illustrative numerical example

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DO - 10.1109/tac.2020.3010770

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