1. Offset-free distributed predictive control based on fuzzy logic: Application to a real four-tank plant
- Author
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Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla. TEP116: Automática y Robótica Industrial, 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, Francisco, Mario, Masero Rubio, Eva, Morales-Rodelo, Keidy, Maestre Torreblanca, José María, Vega, Pastora, Revollar, Silvana, Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla. TEP116: Automática y Robótica Industrial, 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, Francisco, Mario, Masero Rubio, Eva, Morales-Rodelo, Keidy, Maestre Torreblanca, José María, Vega, Pastora, and Revollar, Silvana
- Abstract
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.
- Published
- 2023