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Fuzzy Controller Applied to a Remote Energy Harvesting Emulation Platform.
Camboim, Marcelo Miranda; Villanueva, Juan Moises Maurício; de Souza, Cleonilson Protasio.
Affiliation
  • Camboim MM; Renewable and Alternatives Energies Center (CEAR)/Electrical Engineering Department (DEE)/Campus I, Federal University of Paraiba (UFPB), Joao Pessoa 5045, Brazil.
  • Villanueva JMM; Renewable and Alternatives Energies Center (CEAR)/Electrical Engineering Department (DEE)/Campus I, Federal University of Paraiba (UFPB), Joao Pessoa 5045, Brazil.
  • de Souza CP; Renewable and Alternatives Energies Center (CEAR)/Electrical Engineering Department (DEE)/Campus I, Federal University of Paraiba (UFPB), Joao Pessoa 5045, Brazil.
Sensors (Basel) ; 20(20)2020 Oct 17.
Article in En | MEDLINE | ID: mdl-33080831
In the last decades, a lot of effort has been made in order to improve the use of environmentally friendly and renewable energy sources. In a context of small energy usage, energy harvesting takes place and thermal energy sources are one of its main energy sources because there are several unused heat sources available in the environment that may be used as renewable energy sources. To rapidly evaluate the energy potential of such thermal sources is a hard task, therefore, a way to perform this is welcome. In this work, a thermal pattern emulation system to evaluate potential thermal source in a easy way is proposed. The main characteristics of the proposed system is that it is online and remote, that is, while the thermal-source-under-test is being measured, the system is emulating it and evaluating the generated energy remotely. The main contribution of this work was to replace the conventional Proportional Integral Derivative (PID) controller to a Fuzzy-Proportional Integral (PI) controller. In order to compare both controllers, three tests were carried out, namely: (a) step response, (b) perturbation test, (c) thermal emulation of the thermal pattern obtained from a potential thermal source: tree trucks. Experimental results show that the Fuzzy-PI controller was faster than the PID, achieving a setting time 41.26% faster, and also was more efficient with a maximum error 53% smaller than the PID.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2020 Document type: Article Affiliation country: Brazil Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2020 Document type: Article Affiliation country: Brazil Country of publication: Switzerland