• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1138-1145
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• 2013

A novel predictive current control strategy for a sparse matrix converter is presented. The sparse matrix converter is functionally-equivalent to the direct matrix converter but has a reduced number of switches. The predictive current control uses a model of the system to predict the future value of the load current and generates the reference voltage vector that minimizes a given cost function so that space vector modulation is achieved. The results show that the proposed controller for sparse matrix converters controls the load current very effectively and performs very well through simulation and experimental results.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.1-2
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• 2014

In this paper the partial switching PFC converter which is based on predictive control is proposed. In terms of satisfying the harmonic standard, the predictive control shows a similar performance to the conventional average current mode control PFC in the normal input condition. Moreover, the current harmonic characteristic is insensitive to the distorted input voltage. With predictive control method, novel on-line partial switching strategy is suggested in this paper. Depending on the operating condition, the partial switching PFC converter can boost its output voltage. Also when its efficiency needs to be improved, according to load condition, the partial switching can be achieved. The proposed strategy is proved by the results of FFT and the loss analysis using PSIM 9.0.

• Proceedings of the KIPE Conference
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• 2015.11a
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• pp.209-210
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• 2015

This paper presents a new model predictive control method without the effect of a weighting factor in order to reduce common-mode voltage (CMV) for a three-phase voltage source inverter (VSI). By utilizing two active states with same dwell time during a sampling period instead of one state used in conventional method, the proposed method can reduce the CMV of VSI without the weighting factor. Simulation is carried out to verify the effectiveness of the proposed predictive control method with the aid of PSIM software.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.698-707
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• 2017

This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.175-185
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• 2000

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the rap junctions of freeway with 70mph speed limit. From the traffic analyses, and model construction and verification for delay prediction on the ramp junctions of freeway, the following results were obtained : ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junctions of freeway. ⅲ) The delay-occupancy curve showed a remarkable shift based on the occupancies observed : O$\_$d/〈9% and O$\_$d/$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under O$\_$d/$\geq$9%, but lowly for delay prediction on the ramp junctions of freeway under O$\_$d/〈9%. Rather, the driver characteristics or transportation conditions around the freeway were thought to be a little higher explanatory for the delay prediction under O$\_$d/〈9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.268-269
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• 2017

This paper presents an improved current control strategy for a three-phase grid-connected inverter under distorted grid conditions. Distorted grid condition is undesirable due to negative effects such as power losses and heating problem in electrical equipments. To enhance the power quality of distributed generation systems under such a condition, a modulated finite control set - model predictive control (MFCS-MPC) scheme will be proposed, in which the optimal switching signals of inverter are chosen by online basis using the principle of current error minimization. In addition, the moving average filter (MAF) is used to improve the phase-lock loop in order to obtain the harmonic-free reference currents on the stationary frame. The usefulness of the proposed MFCS-MPC method is proved by the comparative simulation results under different operating conditions.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.219-233
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• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.2
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• pp.159-166
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• 2010

For a grid-connected inverter in distributed generation systems, the current control is essential, and recently, the predictive current control based on a high performance digital signal processors (DSP) to satisfy a fast dynamic response has been widely investigated. However, the performance of predictive current control is degraded by the time delay due to digital implementation, the parameter and measured value errors and the interference of noise, and also theses make system even unstable. Therefore, this paper proposes the predictive current control using grid voltage observer for grid-connected inverter applications. To determine the relevant voltage observer gain, the low-order harmonics of grid voltage are considered, and the effect of filter parameter errors is analyzed. The proposed method has a fast current response capability, the robustness to noise and simple implementation due to voltage sensorless control and the robust current control performance to low-order grid harmonics. The feasibility of the proposed method is verified by simulation and experimental results.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.63-74
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• 2007

In this paper, a reconfigurable controller consisting of a normal controller and a standby controller is designed to control the thermoelectric (TE) power in the SP-100 space reactor. The normal controller uses a model predictive control (MPC) method where the future TE power is predicted by using support vector regression. A genetic algorithm that can effectively accomplish multiple objectives is used to optimize the normal controller. The performance of the normal controller depends on the capability of predicting the future TE power. Therefore, if the prediction performance is degraded, the proportional-integral (PI) controller of the standby controller begins to work instead of the normal controller. Performance deterioration is detected by a sequential probability ratio test (SPRT). A lumped parameter simulation model of the SP-100 nuclear space reactor is used to verify the proposed reconfigurable controller. The results of numerical simulations to assess the performance of the proposed controller show that the TE generator power level controlled by the proposed reconfigurable controller could track the target power level effectively, satisfying all control constraints. Furthermore, the normal controller is automatically switched to the standby controller when the performance of the normal controller degrades.