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Ponencia
Offset-free distributed predictive control based on fuzzy logic: Application to a real four-tank plant
Autor/es | Francisco, Mario
Masero Rubio, Eva Morales-Rodelo, Keidy Maestre Torreblanca, José María Vega, Pastora Revollar, Silvana |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Fecha de publicación | 2023 |
Fecha de depósito | 2024-02-15 |
Publicado en |
|
ISBN/ISSN | 978-171387234-4 2405-8963 |
Resumen | This paper proposes an offset-free distributed implementation of a model predictive controller that employs fuzzy negotiation between agents. The scheme is based on model augmentation with additional disturbances to enable ... This paper proposes an offset-free distributed implementation of a model predictive controller that employs fuzzy negotiation between agents. The scheme is based on model augmentation with additional disturbances to enable zero-offset tracking. Moreover, we code the negotiation criteria as a set of suitable fuzzy rules and consider stability and feasibility guarantees in the controller design for the linearized subsystems. We applied the method to an experimental four-tank plant, showing its effectiveness despite the coupling between subsystems and system-model mismatch. |
Agencias financiadoras | Spanish government under the Predoctoral Training Program for University Staff Nº FPU18/04476 Spanish government project PID2019-105434RB-C31 Spanish government project PID2020-119476RBI00 Spanish government project FS/11-2021 European Research Council (ERCAdG) under the H2020 program OCONTSOLAR, Nº 789051 |
Identificador del proyecto | FPU18/04476
PID2019-105434RB-C31 PID2020-119476RBI00 FS/11-2021 EU H2020 Nº 789051 – Project OCONSOLAR |
Cita | Francisco, M., Masero Rubio, E., Morales-Rodelo, K., Maestre Torreblanca, J.M., Vega, P. y Revollar, S. (2023). Offset-free distributed predictive control based on fuzzy logic: Application to a real four-tank plant. En 22nd IFAC World Congress (3247-3252), Yokohama, Japan: Elsevier. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
maestre-torreblanca_2023_offset.pdf | 2.202Mb | [PDF] | Ver/ | |
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