• Journal of Power Electronics
• /
• v.14 no.3
• /
• pp.444-457
• /
• 2014

This paper presents the design and realization of a digital PV simulator with a Push-Pull Forward (PPF) circuit based on the principle of modular hardware and configurable software. A PPF circuit is chosen as the main circuit to restrain the magnetic biasing of the core for a DC-DC converter and to reduce the spike of the turn-off voltage across every switch. Control and I/O interface based on a personal computer (PC) and multifunction data acquisition card, can conveniently achieve the data acquisition and configuration of the control algorithm and interface due to the abundant software resources of computers. In addition, the control program developed in Matlab/Simulink can conveniently construct and adjust both the models and parameters. It can also run in real-time under the external mode of Simulink by loading the modules of the Real-Time Windows Target. The mathematic models of the Push-Pull Forward circuit and the digital PV simulator are established in this paper by the state-space averaging method. The pole-zero cancellation technique is employed and then its controller parameters are systematically designed based on the performance analysis of the root loci of the closed current loop with $k_i$ and $R_L$ as variables. A fuzzy PI controller based on the Takagi-Sugeno fuzzy model is applied to regulate the controller parameters self-adaptively according to the change of $R_L$ and the operating point of the PV simulator to match the controller parameters with $R_L$. The stationary and dynamic performances of the PV simulator are tested by experiments, and the experimental results show that the PV simulator has the merits of a wide effective working range, high steady-state accuracy and good dynamic performances.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.457-461
• /
• 2001

Advantages of switched reluctance motor(SRM) drives make it an attractive candidate for replacing adjustable speed ac and dc drives in both industrial and consumer applications. Furthermore, a simple, low cost and robust SRM drive can be efficiently operated in the hostile environment of an automobile. Generally, the speed control of SRM has a large step change or large torque reference, the output of its PI controller is often saturated. When this happens, the integral state is not consistent with the SRM input, while may give rise to the windup phenomenon. This paper proposes anti-windup control method for SRM speed control system by hysteresis current controlled asymmetry bridge converter. The experimental results show that the speed response has much improved performance, such as a small overshoot and fast settling time at the acceleration and particulary deceleration period with braking mode.

• Proceedings of the KIEE Conference
• /
• 2009.04b
• /
• pp.32-34
• /
• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.404-407
• /
• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation even under ideal field oriented conditions. This paper is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.14 no.3
• /
• pp.29-37
• /
• 2000

In this paper, the thrust control of PWM Inverter-fed SLIM(Single-sided Linear Induction Motor) is achieved by vector control and PID control with DSP(TMS320C32). SLIM which used as a conveyor has required the quick response and the constant operating without air gap trembling while it conveys load.Thus, SLIM should have the smallest trembling of air gap length. First, voltage equations for SLIM are calculated from the proposed equivalent circuit in this peper, and not only the exciting current but also the thrust component are obtained from them. The thrust current ripple can be reduced by the vector controller using a slip angle frequency, and the PID controller is also use for the position control.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.12 no.3
• /
• pp.267-275
• /
• 2007

This paper presents about energy input and output modeling for a flywheel energy storage system that can store and supply mechanical energy, which is emerging as one of clean energy sources, and the analysis and control of a PWM inverter system. Moreover, this paper describes flywheel's characteristics related to variations of mechanical and electrical parameters like as voltage and current versus speed characteristics formed as numerical formula and thus simulate behaviour-status of flywheel energy. Also for comparison and analysis between PI control and PDFF control, the modeling, design and analysis to the single-phase full bridge inverter with double loop feedback control is accomplished through numerical description and simulation. Finally, under load condition 0.1[pu], 1[pu]. it is validated that harmonic characteristics for voltage and current wave is controlled within 5% below even dynamics condition.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.620-626
• /
• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.5 no.5
• /
• pp.419-426
• /
• 2000

Generally diode rectifier has been used as Preregulator of arc- welding machine. Its defect is the generation of high current harmonics which result In utility pollution. In this parer, using the three-phase PWM converter, the input performance of arc-welding machine is improved by increasing the input power factor. When the diode rectifier in the arc-welding machine is replaced with three-phase PWM converter, PWM converter should control DC voltage of the output side. If PI controller is used for the output DC voltage regulator, the output DC voltage has high ripple voltage due to the instantaneous load variation in the arc-welding machine. In this paper, the feedforward compensator has been introduced to reduce the DC voltage ripple. It lessens the influence of load current which is the disturbance of the output DC voltage regulator. Theoretical prediction of this analysis has been verified by comparing with experimental data

• Journal of Industrial Technology
• /
• v.40 no.1
• /
• pp.13-18
• /
• 2020

Lithium-ion batteries have a small volume, light weight and high energy density, maximizing the utilization of mobile devices. It is widely used for various purposes such as electric bicycles and scooters (e-Mobility), mass energy storage (ESS), and electric and hybrid vehicles. To date, lithium-ion batteries have grown to focus on increasing energy density and reducing production costs in line with the required capacity. However, the research and development level of lithium-ion batteries seems to have reached the limit in terms of energy density. In addition, the charging time is an important factor for using lithium-ion batteries. Therefore, it was urgent to develop a high-speed charger to shorten the charging time. In this thesis, a discharger was fabricated to evaluate the capacity and characteristics of Li-ion battery pack which can be used for e-mobility. To achieve this, a smart discharger is designed with a combination of active load, current sensor, and temperature sensor. To carry out this thesis, an active load switching using sensor control circuit, signal processing circuit, and FET was designed and manufactured as hardware with the characteristics of active discharger. And as software for controlling the hardware of the active discharger, a Raspberry Pi control device and a touch screen program were designed. The developed discharger is designed to change the 600W capacity battery in the form of active load.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.25 no.3
• /
• pp.213-218
• /
• 2020

In this study, we propose a control algorithm to reduce the unbalanced characteristics of a three-phase system power caused by the unbalanced load of the AC electric railway. Then, we verify its performance through the design of a power compensator and experiments applying it. Like electric railway systems, a Scott transformer is applied, and the load and single-phase back-to-back converters are connected to the M-phase and T-phase outputs. The back-to-back converter monitors the difference in active power between the unbalanced loads in real-time and compensates for the power by using bidirectional characteristics. The active power is performed through PI control in the synchronous coordinate system, and DC link overall voltage and voltage balancing control are controlled jointly by M-phase and T-phase converters to improve the responsiveness of the system. To verify the performance of the proposed power compensation device, an experiment was performed under the condition that M-phase 5 kW and T-phase 1 kW unbalanced load. As a result of the experiment, the unbalance rate of the three-phase current after the operation of the power compensator decreases by 58.66% from 65.04% to 6.38%, and the excellent performance of the power compensator proposed in this study is verified.