Dynamic performance improvement of an ultra-lift Luo DC–DC converter by using a type-2 fuzzy neural controller

Publication Type:
Journal Article
Citation:
Computers and Electrical Engineering, 2018, 69 pp. 171 - 182
Issue Date:
2018-07-01
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© 2018 Due to the uncertainty associated with the structure and electrical elements of DC–DC converters and the nonlinear performance of these modules, designing an effective controller is highly complicated and also technically challenging. This paper employs a new control approach based on type-2 fuzzy neural controller (T2FNC) in order to improve the dynamic response of an ultra-lift Luo DC–DC converter under different operational conditions. The proposed controller can rapidly stabilize the output voltage of converter to expected values by tuning the converter switching duty cycle. This controller can tackle the uncertainties associated with the structure of converters, measured control signals and measuring devices. Moreover, a new intelligent method based on firefly algorithm is applied to tune the parameters of T2FNC. In order to demonstrate the effectiveness of the proposed control approach, the proposed controller is compared to PI and fuzzy controllers under different operational conditions. Results validate efficiency of proposed T2FNC.
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