Artículo
Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets
Autor/es | Cotorruelo, Andres
Rodríguez Ramírez, Daniel Limón Marruedo, Daniel Garone, Emanuele |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Fecha de publicación | 2021 |
Fecha de depósito | 2022-09-29 |
Publicado en |
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Resumen | This article presents an extension to the nonlinear
model predictive control (MPC) for tracking scheme able to guarantee convergence even in cases of nonconvex output admissible
sets. This is achieved by incorporating a ... This article presents an extension to the nonlinear model predictive control (MPC) for tracking scheme able to guarantee convergence even in cases of nonconvex output admissible sets. This is achieved by incorporating a convexifying homeomorphism in the optimization problem, allowing it to be solved in the convex space. A novel class of nonconvex sets is also defined for which a systematic procedure to construct a convexifying homeomorphism is provided. This homeomorphism is then embedded in the MPC optimization problem in such a way that the homeomorphism is no longer required in closed form. Finally, the effectiveness of the proposed method is showcased through an illustrative example |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Ministerio de Ciencia e Innovación (MICIN). España Fonds De La Recherche Scientifique - FNRS |
Identificador del proyecto | DPI2016-76493-C3-1-R
PID2019-106212RB-C41 F.4526.17 |
Cita | Cotorruelo, A., Rodríguez Ramírez, D., Limón Marruedo, D. y Garone, E. (2021). Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets. IEEE Transactions on Automatic Control, 66 (8), 3726-3732. |
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