Neural control and transient analysis of the LCL-type resonant converter
Authors: Zouggar, S., Nait Charif, H. and Azizi, M.
Journal: EPJ Applied Physics
Volume: 11
Issue: 1
Pages: 21-27
ISSN: 1286-0042
DOI: 10.1051/epjap:2000142
Abstract:This paper proposes a generalised inverse learning structure to control the LCL converter. A feedforward neural network is trained to act as an inverse model of the LCL converter then both are cascaded such that the composed system results in an identity mapping between desired response and the LCL output voltage. Using the large signal model, we analyse the transient output response of the controlled LCL converter in the case of large variation of the load. The simulation results show the efficiency of using neural networks to regulate the LCL converter.
Source: Scopus
Neural control and transient analysis of the LCL-type resonant converter
Authors: Zouggar, S., Nait-Charif, H. and Azizi, M.
Journal: The European Physical Journal - Applied Physics
Volume: 11
Pages: 21-27
ISSN: 1286-0042
DOI: 10.1051/epjap:2000142
Abstract:This paper proposes a generalised inverse learning structure to control the LCL converter. A feedforward neural network is trained to act as an inverse model of the LCL converter then both are cascaded such that the composed system results in an identity mapping between desired response and the LCL output voltage. Using the large signal model, we analyse the transient output response of the controlled LCL converter in the case of large variation of the load. The simulation results show the efficiency of using neural networks to regulate the LCL converter.
http://www.edpsciences.org/10.1051/epjap:2000142
Source: Manual
Preferred by: Hammadi Nait-Charif