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One of the important role for dc-dc converters is to regulate output voltage against the transient variation of input voltage. Recently, renewable energy becomes popular and renewable power generators are connected to the dc power grid directly, dc bus voltage is affected from them. Therefore, the improvement of the transient response against the variation of the dc bus voltage is required to control...
This paper studies about computational burden of a reference modified PID with a neural network prediction for dc-dc converters. Flexible control methods are required to realize a superior transient response since the converter has a nonlinear behavior. However, the computational burden becomes a problem to implement the control to computation devices. In this paper, the neural network is adopted...
This paper proposes a current balance control in parallel operation using neural network control in addition to the conventional digital soft-start control for dc-dc converters. The neural network predictor is used in the average current balance control to improve the voltage drop when the current balance operation starts. In the proposed method, the neural network is trained to predict the output...
In this paper, a reference modification method for the PID control is studied to improve the transient response of the output voltage of the power converter using weighted prediction information with a neural network predictor. Several predictions of the output voltage with the neural network are used to obtain the modified reference value in the PID control by minimizing the objective function. The...
In this paper, a novel digital soft-start control method which employs a reference modification with a neural network predictor is presented to improve the transient characteristics in parallel operated dc-dc converters. To reduce the power consumption in parallel operated dc-dc converters, the mode of them is changed frequently from stand-by mode to operating mode, or vice versa. In the transient...
The aim of this paper is to give a comparative study on the effect of neural network based reference modification method for a digitally controlled dc-dc converter when circuit parameters and PID control parameters are changed. In general, the parameters of PID control are selected to satisfy both stable regulation of static state and followability of transient state. The selection of parameter values...
The purpose of this paper is to propose a novel digital control method of dc-dc converter where a neural network predictor based reference modification is adopted to improve the transient response in coordination with a conventional PID control. Power supplies for electrical equipment such as computing server, UPS, and so forth, requires a superior control method which can obtain stable operation...
This paper presents a neural network based PID parameter selection control to improve the transient response of dc-dc converters. In the conventional PID control, parameters of it such as proportional, integral, and differential coefficients are selected as fixed parameters to regulate both transient and steady-state characteristics simultaneously as much as possible. The parameter setting of PID...
This study presents a novel adaptive control based on a neural network for dc -- dc converters. The control method is required to adapt to changes of conditions to obtain high performance dc -- dc converters. In this study, the neural network control is adopted to improve the transient response of dc -- dc converters. It woks in coordination with a conventional PID control to realize a high adaptive...
The purpose of this paper is to show performance characteristics of the reference modification control dc-dc converter which uses neural network and model controls. In the presented method, the neural network controller is used to modify the reference in the proportional control term of the conventional PID control. The neural network controller is repeatedly trained using former predicted data to...
The purpose of this paper is to present a new digital control method for dc-dc converters by reference modification with the neural network predictor. In the proposed method, the reference in the proportional control term of the conventional PID control is modified using the neural network predictor during the transient interval. The neural network is repeatedly trained to predict the output voltage...
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