PD-Type-2 Fuzzy Neural Network Based Control of a Super-Lift Luo Converter Designed for Sustainable Future Energy Applications

Gani A.

Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, İstanbul, Turkey, 22 - 24 August 2023, vol.758 LNNS, pp.561-568 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 758 LNNS
  • Doi Number: 10.1007/978-3-031-39774-5_62
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.561-568
  • Keywords: Intelligence and Sustainable Future Energy, PD-Type-2 Fuzzy-Neural Network, Super-Lift Luo Converter
  • Kayseri University Affiliated: Yes


In line with sustainable future energy applications, the present study aims to model and control a super-lift Luo power converter and to convert a low direct current input voltage to a high direct current output voltage. To this end, using Matlab/Simulink environment, a super-lift luo power converter and PD-type-2 fuzzy-neural network (PD-T2FNN) were designed. A PD-T2FNN was used to analyze the super-lift performance of luo power converter against different operational conditions. Different operational conditions were considered as ramp set-point reference voltage change, step set-point input voltage change and internal disturbance (load) change. Performances of the PD-T2FNN was evaluated in terms of settling time, overshoot, undershoot and recovery time. The simulation findings clearly demonstrated that PD-T2FNN displayed an effective performance in terms of its durability against the above-mentioned operational conditions. It can be thus concluded that the super-lift luo power converter offers a feasible system for intelligent and sustainable future energy applications such as fuel cell and photovoltaic systems with a very low input voltage.