TY - JOUR

T1 - Robust Stability of Barrier-Based Model Predictive Control

AU - Petsagkourakis, Panagiotis

AU - Heath, William P.

AU - Carrasco, Joaquin

AU - Theodoropoulos, Constantinos

PY - 2021/4/1

Y1 - 2021/4/1

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

U2 - 10.1109/tac.2020.3010770

DO - 10.1109/tac.2020.3010770

M3 - Erthygl

VL - 66

SP - 1879

EP - 1886

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

SN - 2334-3303

IS - 4

ER -