• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.8
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• pp.42-49
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• 2012

Grid-connected photovoltaic generator system requires high performance PCS(Power Conditioning System) according to the standard of 'Distributed Generation Grid-Connected Technology Standards'. This paper presents the MPPT control method which improves output efficiency through fast tracking to the maximum power point of PV and a reduced self-excited vibration. Secondly, in this paper DVR function was applied to PCS to compensate the voltage sag frequently happening for a power system. The proposed PCS control is analyzed and compared to conventional PCS operating characteristic, the various insolation and loads, and voltage sag condition through PSIM tool. It proves the utility.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1949-1950
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• 2006

In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.195-200
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• 1994

This paper presents a nonlinear adaptive control approach to a 4-point attraction magnetic levitation system using the local coordinates transformation and neural network. Based on local coordinates transformations, the magnetic levitation system can be represented in a state magnetic levitation system can be represented in a state space from of a 4-input 4-output. Neural networks which are defined in the new coordinates are used to learn the nonlinear functions of the system which are defined in the new coordinats also. The parameters of the neural networks are updated in an on-line manner according to an augmented tracking error. The simulation results are reported in this paper.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2656-2658
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• 1999

This paper presents a control scheme for a three-phase PWM converter system without any voltage sensors. Two input currents and one load current are measured. In a general PWM converter system, the required AC input and DC output voltage values in order to control the converter are estimated using the differential equations of the converter from the measured input currents and load current values in the switch modes of the converter circuit. The PI controller is used as DC voltage controller and sinusoidal tracking controller which tracks directly AC input current is used as input current controller. The Proposed method is verified by simulations. This paper describes the estimation method and configuration of the controller, and discusses steady state and transient performances of the converter

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.161-167
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• 2001

This paper presents an approach to nonlinear engine idle controller and intake manifold absolute pressure(MAP) observer based on mean torque production model. A stable engine idle speed is important in that the unstable engine Idle mode can make engine to drooping or stall state. A sliding fuzzy controller has been designed to control engine idle speed under load disturbance. A sliding observer is also developed to estimate the intake manifold absolute pressure and compared with the actual MAP sensor value. The sliding mode observer has shown good robustness and good tracking performance. The inputs of sliding fuzzy controller are the errors of rpm and MAP. The output is a duty cycle(DC) for driving a idle speed control valve(ISCV).

• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.94-101
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• 2015

This paper presents findings on the second-order sliding-mode controller for a nuclear research reactor. Sliding-mode controllers for nuclear reactors have been used for some time, but higher-order sliding-mode controllers have the added advantage of reduced chattering. The nonlinear model of Pakistan Research Reactor-1 has been used for higherorder sliding-mode controller design and performance evaluation. The reactor core is simulated based on point kinetics equations and one delayed neutron groups. The model assumes feedback from lumped fuel and coolant temperatures. The effect of xenon concentration is also considered. The employed method is easy to implement in practical applications, and the second-order sliding-mode control exhibits the desired dynamic properties during the entire output-tracking process. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2383-2385
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• 2000

It is proposed a new algorithm for a neural network adaptive tracking control scheme to improve performance in this paper. In supervisory control scheme, the upper and lower bound of the parameters are directly estimated by using RBF neural network without their information, and the weighting parameters of the control input are adjusted on-line by adaptation laws. As a result, the proposed algorithm assured that the output errors go to zero without relation to existing minimum approximation errors and disturbances. The effectiveness of the proposed algorithm is demonstrated through the simulation of one-link rigid robotics manipulator.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1269-1276
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• 2014

The main objective of this paper is to design DC-DC MPPT circuit using chaotic pulse width modulation to track maximum power from solar PV module for space application. The direct control method of tracking is used to extract maximum power. The nominal duty cycle of the main switch of DC-DC SEPIC converter is adjusted so that the solar panel output impedance is equal to the input resistance of the SEPIC converter which results better spectral performance in the tracked voltages when compared to conventional PWM control. The conversion efficiency of the proposed MPPT system is increased when CPWM is used as a control scheme

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.153-156
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• 2003

This short paper suggests a control strategy using a stepwise fuzzy moving sliding surface. The moving surface is a Sugeno-type fuzzy system that has the angle of state error vector and the distance from the origin in the phase plane as inputs and a first-order linear differential equation as an output. The surface initially passes arbitrary initial states and subsequently moves towards a predetermined surface via rotating or shifting. the proposed method reduces the reaching and tracking time and improves robustness. The asymptotic stability of the fuzzy sliding surface is proved. The validity of the proposed control scheme is shown in computer simulation for a second-order nonlinear system.