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This paper proposes a sliding-mode-based direct power control (DPC) method in a three-phase boost rectifier without the use of a voltage sensor. This sliding-mode-based DPC is used to improve transient-state response characteristics. This DPC can eliminate voltage sensors by calculating a voltage using a sensorless method, thus considerably reducing cost. This DPC first presents an effective algorithm that does not significantly affect the previous performance and does not need a voltage sensor. Thereafter, the effectiveness of the algorithm is verified by simulations and experiments.

This paper proposes a gain scheduling method that improves the stability of grid-connected systems employing an LCL-filter. The method adjusts the current controller gain through an estimation of the grid impedance in order to reduce the resonance that occurs when using an LCL-filter to reduce switching harmonics. An LCL-filter typically has a frequency spectrum with a resonance peak. A change of the grid-impedance results in a change to the resonant frequency. Therefore an LCL-filter needs a damping method that is applicable when changing the grid impedance for stable system control. The proposed method instantaneously estimates the grid impedance and observes the resonant frequency at the same time. Consequently, the proposed method adjusts the current controller gain using a gain scheduling method in order to guarantee current controller stability when a change in the resonant frequency occurs. The effectiveness of the proposed method has been verified by simulations and experimental results.

This study proposes a model-based predictive control for interleaved multi-phase DC/DC converters. The power values necessary to adjust the output voltage in the succeeding are predicted using a converter model. The output power is controlled by selecting the optimal duty cycle. The proposed method does not require controller loops and modulators for converter switching. This method can control the converter by calculating the optimal duty cycle, which minimizes the error between the reference and actual output voltage. The effectiveness of the proposed method is verified through simulations and experiments.

In recent years, fault tolerance has become one of the most interesting topics because the open-switch faults rise to unbalance of the AC input currents and unable to control DClink voltage that can cause serious damage to the connected application. This paper proposes a model predictive direct power control (MPDPC) method to tolerance control using a neutralpoint clamped (NPC) topology in a switch fault situation. This method uses the cost function concerning active power and reactive power to select a voltage vector and can detect the openswitch fault without using additional devices or complex calculations. Simulations are carried out to confirm the reliability of the proposed fault-detection method.

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The MPPT algorithm using neuro-fuzzy controller is proposed to improve the performance of fuzzy controller in this paper. The width of membership function and fuzzy rule have an effect on the performance of fuzzy controller. The neuro-fuzzy controller has the response characteristic which is superior to the existing fuzzy controller, because of using the optimal width of the fuzzy membership function through the neural learning. The superior control characteristic of a proposed algorithm is confirmed through simulation and experiment results.