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Three-phase boost ac-to-dc rectifiers have been widely used for rapid transit systems, adjustable speed drives (ASD) and uninterruptible power supplies (UPS). In the case of getting a unity power factor, reducing switching count for devices, and fulfilling proper performance requirements of steady state, a switching algorithm that used a fixed switching frequency had been detailed in a previous thesis of graduate in this laboratory. However, how to design a controller to further improve the dynamic performance of the rectifier has not been finished yet.
AC/DC converters are highly nonlinear and time varying. Since the system parameters could vary with different operating states, the conventional proportional integral controller cannot be adjusted with respect to the system response. With the ability to learn, adapt and provide wider dynamic range a fuzzy controller could achieve the robust control on the nonlinear system. The fuzzy controller is similar to artificial intelligence that will be the bridge of brain with computer. However, the conventional fuzzy controllers need to provide complicated rules to establish the whole fuzzy rules based on the method of trial-and-error. The control scheme proposed in this thesis is based on a self-tuning fuzzy controller and a self-tuning fuzzy identifier. It adjusts the membership function by taking back propagation algorithm. Comparisons are made by the simulation of fuzzy controller and pure PI controller under steady state and dynamic operations.
The simulation results demonstrate that fuzzy controllers can effectively control the ac-to-dc switching converter with high power factor. It has good dynamic performance of output voltage tracking and current distribution for different loading conditions. It could also be operated in a higher desired DC output voltage with the same source voltage and the same condition of the controlled switching converter.

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