Reconfiguration strategy for a DC-DC boost converter using sliding mode observers and fault identification with a neural network

Authors

  • Diego S. Carneiro Escola de Engenharia de São Carlos, Universidade de São Paulo, SP
  • Lucas Jonys R. Silva Escola de Engenharia de São Carlos, Universidade de São Paulo, SP
  • Flávio A. Faria Universidade Estadual Paulista (Unesp), Faculdade de Engenharia, Ilha Solteira, SP
  • Rafael F. Q. Magossi Centro Federal de Educação Tecnológica Celso Suckow da Fonseca, CEFET, Nova Friburgo, RJ
  • Vilma A. Oliveira Escola de Engenharia de São Carlos, Universidade de São Paulo, SP

DOI:

https://doi.org/10.20906/sbai.v1i1.2741

Keywords:

DC-DC converters, sensor faults, sliding mode control, sliding mode observer, pattern recognition

Abstract

In this paper, a method for the reconfiguration of the operation of DC-DC boost converters is proposed using sliding mode observers (SMOs). Open sensor and high gain faults are analyzed. In the fault identification algorithm, a neural network with pattern recognition is proposed. The reconfiguration strategy consists in two auxiliary sliding mode state observers to estimate sensor values in the presence of faults, in order to guarantee a proper switching control law to keep the system stable.

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Published

2021-10-20

Issue

Vol. 1 No. 1 (2021): SBAI2021

Section

Articles