@article{MAKHILLIJSC20149321195,
    title = {Comparative Evaluation of Intelligent Controller for a Buck-Boost Converter},
    journal = {International Journal of Soft Computing},
    volume = {9},
    number = {3},
    pages = {143-150},
    year = {2014},
    issn = {1816-9503},
    doi = {ijscomp.2014.143.150},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2014.143.150},
    author = {M.V. and},
    keywords = {Buck-Boost converter,fuzzy controller,neural network,PI controller,state},
    abstract = {This study compares the performance of neural network controller, fuzzy logic 
  controller and PI controller applied to a buck boost converter. The design of 
  neural network controller is based on online learning method using Back Propagation 
  algorithm. Design of fuzzy logic controller is based on heuristic knowledge 
  of the converters behavior. The design of PI control is based on the frequency 
  response of the converter. The controllers are developed to stabilize the output 
  voltage of the converter and improve the performance of the buck-boost converter 
  during transient operations. Simulation results obtained during load and line 
  variations shows that the online neural network control was able to achieve 
  faster transient response and had a stable steady state response.}
    }