• Journal of Power Electronics
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• 제7권2호
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• pp.140-145
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• 2007

The negative output elementary Luo converter is a newly developed DC-DC converter. Due to the time-varying and switching nature of the above converter, its dynamic behavior becomes highly non-linear. Conventional controllers are incapable of providing good dynamic performance for such a converter and, hence, a neural network is utilized as a controller in this work. The performance of the chosen Luo converter using PI versus neuro controls is compared under load and line disturbances using MATLAB and TMS320F2407 DSP. The results validate the superiority of the developed neuro controller.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1082-1089
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• 2017

Negative output elementary super lift Luo converter (NOESLLC), which has the significant advantages including high-voltage transfer gain, high efficiency, high power density, and reduced output voltage/inductor current ripples when compared to the traditional DC-DC converters, is an attractive DC-DC converter for the field of negative DC voltage applications. In this study, in consideration of the voltage across the energy transferring capacitor changing abruptly at the beginning of each switching cycle, the improved averaged model of the NOESLLC operating in continuous conduction mode (CCM) is established. The improved DC model and transfer functions of the system are derived and analyzed. The current mode control is applied for this NOESLLC. The results from the theoretical calculations, the PSIM simulations and the circuit experiments show that the improved DC model and transfer functions here are more effective than the existed ones of the NOESLLC to describe its real dynamical behaviors.