• Journal of Power Electronics
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• v.19 no.2
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• pp.380-393
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• 2019

Traditional boost converters have difficulty realizing high efficiency and high voltage gain conversion due to 1) extremely large duty cycles, 2) high voltage and current stresses on devices, and 3) low conversion efficiency. Therefore, a function decoupling high voltage gain DC/DC converter composed of a DC transformer (DCX) and an auxiliary converter is proposed. The role of DCX is to realize fixed gain conversion with high efficiency, whereas the role of the auxiliary converter is to regulate the output voltage. In this study, different forms of combined high voltage gain converters are compared and analyzed, and a structure is selected for the function decoupling high voltage gain converter. Then, topologies and control strategies for the DCX and auxiliary converter are discussed. On the basis of the discussion, an optimal design method for circuit parameters is proposed, and design procedures for the DCX are described in detail. Finally, a 400 W experimental prototype based on the proposed optimal design method is built to verify the accuracy of the theoretical analysis. The measured maximum conversion efficiency at rated power is 95.56%.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.65-73
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the Optical Society of Korea Conference
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• 1991.06a
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• pp.35-40
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• 1991

In this paper, a new adaptive learning algorithm, Training by Adaptive Gain (TAG) for optical implementation of large-sized neural networks has been developed and its electro-optical implementation for 2-dimensional input and output neurons has been demostrated. The 4-dimensional global fixed interconnections and 2-dimensional adaptive gain-controls are implemented by multi-facet computer generated holograms and LCTV spatial light modulators, respectively. When the input signals pass through optical system to the output classifying layer, the TAG adaptive learning algorithm is implemented by a personal computer. The system classifies three 5$\times$5 input patterns correctly.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1241-1248
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• 2004

A controller of wheeled mobile robot(WMR) based on Lyapunov theory is designed and a Fuzzy-Neural Network algorithm is applied to this system to adjust controller gain. In conventional controller of WMR that adopts fixed controller gain, controller can not pursuit trajectory perfectly when initial condition of system is changed. Moreover, acquisition of optimal value of controller gain due to variation of initial condition is not easy because it can be get through lots of try and error process. To solve such problem, a Fuzzy-Neural Network algorithm is proposed. The Fuzzy logic adjusts gains to act up to position error and position error rate. And, the Neural Network algorithm optimizes gains according to initial position and initial direction. Computer simulation shows that the proposed Fuzzy-Neural Network controller is effective.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.321-326
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• 1993

A gain scheduling approach for the suspension control of a nonlinear MAGLEV System is presented. We show that this technique is ver useful for improving not only performance to the operational disturbances originating aerodynamic force but also robustness to the uncertainty of payload. As a scheduling variable, even though the external disturbance need to be estimated in real time, but the additive measurement is not required to do it. Some simulations show that the gain scheduling control system performs very well comparing with other method using a nonlinear feedback linearization or a fixed gain linear feedback.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.60-67
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• 1998

In this paper, a gain scheduling method of PID controller is proposed using fuzzy logic for balancing control of an inverted pendulum. First, gains of PID controller are calculated using pole-placement technique for the linearized model of an inverted pendulum and these gains are modified by fuzzy logic throughout control operations. A PD controller is used by switching near the set-point to improve the performance. It is illustrated by simulations that the proposed hybrid fuzzy control method yidels smaller rising time and overshoot compared to the fixed-gain PID controller or fuzzy logic-based only PID controller.

• The KSFM Journal of Fluid Machinery
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• v.18 no.1
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• pp.59-64
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• 2015

The pitch control system in wind turbines becomes more and more important as the wind turbines are larger in multi-MW size. PI controller has been applied in most pitch controllers and it has been known that gain-scheduling is essential for pitch control of wind turbines. A demo model of 2 MW wind turbine which represents the whole dynamics of wind turbine including dynamic behaviors of blade, tower and rotational shaft is given in the commercial Bladed S/W for real wind turbines. In this paper, some results on step responses of the pitch PI controller and effectiveness of gain-scheduled pitch PI controller are presented through the Bladed S/W for the 2 MW wind turbine.

• Journal of Power Electronics
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• v.16 no.1
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• pp.277-286
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• 2016

This paper offers two Maximum Power Point Tracking (MPPT) systems for Photovoltaic (PV) applications. The first MPPT method is based on a fixed frequency Model Predictive Control (MPC). The second MPPT technique is based on the Predictive Hysteresis Control (PHC). An experimental demonstration shows that the proposed techniques are fast, accurate and robust in tracking the maximum power under different environmental conditions. A DC/DC converter with a high voltage gain is obligatory to track PV applications at the maximum power and to boost a low voltage to a higher voltage level. For this purpose, a high gain Switched Inductor Quadratic Boost Converter (SIQBC) for PV applications is presented in this paper. The proposed converter has a higher gain than the other transformerless topologies in the literature. It is shown that at a high gain the proposed SIQBC has moderate efficiency.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.755-760
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• 2013

The dynamics of the winder roller of a roll-to-roll printing system for printed electronics is a time-varying system because of the variation of the winder roller radius owing to rewinding or unwinding of the web. Therefore, an adaptive control method considering the time-variant characteristics is required for precise tension control. In this study, the variable PID gain method is applied to the actual roll-to-roll system and verified by experiments for unwinder tension control. The required value of the winder roller radius for the application of the variable PID gain is estimated from the measurement of the winder tension and winder motor torque. The simulation results as well as experimental results show that the fixed PID gain control cannot stabilize the tension of the winder roller with varying winder roller radius. On the other hand, the variable PID gain method can control the tension of the winder roller regardless of the winder roller radius.