LPV-Filtered Predictive Control Design for Fault-Tolerant Energy Management

Marcelo Menezes Morato1, Paulo Mendes2, Julio Elias Normey-rico3, Carlos Bordons4

  • 1Universidade Federal de Santa Catarina
  • 2Federal University of Santa Catarina
  • 3Federal Univ of Santa Catarina
  • 4Universidad de Sevilla



Poster Session


11:45 - 12:20 | Wed 24 Apr | Fauna | WeS2

Poster B

09:00 - 10:20 | Thu 25 Apr | Hallway | ThSS

All Posters Session

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This study presents a Filtered Model-based Predictive Control method for the Fault- Tolerant Energy Management of a sugarcane microgrid; such plant has several renewable sources (solar, wind and biomass power), being subject to different operational constraints and load demands. The proposed control policy ensures that these demands are met at every iteration, despite the presence of faults, coordinating which energy source to use, maximizing the use the renewables according to contract rules. The proposed predictive controller is synthesized with a fault-free model of the plant and coupled with a feedback low-pass Linear Parameter Varying (LPV) filter that is scheduled according to the level of faults detected upon the system. Such system is compared to a standard predictive controller, displaying much improved behavior.

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