• Proceedings of the KIEE Conference
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• 1983.07a
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• pp.135-138
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• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• Journal of Power Electronics
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• v.19 no.1
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• pp.220-233
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• 2019

This work aims to study and analyze the various operating modes of universal power converter which is powered by solar and thermoelectric generators. The proposed converter is operated in a DC-DC (buck or boost mode) and DC-AC (single phase) inverter with high efficiency. DC power sources, such as solar photovoltaic (SPV) panels, thermoelectric generators (TEGs), and Li-ion battery, are selected as input to the proposed converter according to the nominal output voltage available/generated by these sources. The mode of selection and output power regulation are achieved via control of the metal-oxide semiconductor field-effect transistor (MOSFET) switches in the converter through the modified stepped perturb and observe (MSPO) algorithm. The MSPO duty cycle control algorithm effectively converts the unregulated DC power from the SPV/TEG into regulated DC for storing energy in a Li-ion battery or directly driving a DC load. In this work, the proposed power sources and converter are mathematically modelled using the Scilab-Xcos Simulink tool. The hardware prototype is designed for 200 W rating with a dsPIC30F4011 digital controller. The various output parameters, such as voltage ripple, current ripple, switching losses, and converter efficiency, are analyzed, and the proposed converter with a control circuit operates the converter closely at 97% efficiency.

• Journal of Power Electronics
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• v.19 no.1
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• pp.190-200
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• 2019

The flyback converter, which can be regarded as a nonlinear time-varying system, has complex dynamics and nonlinear behaviors. These phenomena can affect the stability of the converter. To simplify the modeling process and retain the information of the output capacitor branch, a special sampled-data model of a peak current-mode (PCM) controlled flyback converter is established in this paper. Based on this, its dynamic behaviors are analyzed, which provides guidance for designing the circuit parameters of the converter. With the critical stability boundary equation derived by a Jacobian matrix, the stable operation range with a varied output capacitor, proportional coefficient of error the amplifier, input voltage, reference voltage and slope of the compensation ramp of a PCM controlled flyback converter are investigated in detail. Research results show that the duty ratio should be less than 0.5 for a PCM controlled flyback converter without ramp compensation to operate in a stable state. The stability regions in the parameter space between the output capacitor and the proportional coefficient of the error amplifier are enlarged by increasing the input voltage or by decreasing the reference voltage. Furthermore, the ramp compensation also can extend to the stable region. Finally, time-domain simulations and experimental results are presented to verify the theoretical analysis results.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.285-287
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• 2006

The paper treats the nonlinear robust control of Chua's circuit having Chuar's diode as an element based on the internal model principle. The Chua's diode has unknown nonlinear parameters and the circuits parameters are alos assumend unknown. Nonlinear regulator equations are established to obtain 3-fold equilibrium equations on which the output error is zero. Also an internal model of the 3-fold exosystem is constructed for obtaining the control law. Pole Placement method is used for obtaining the feeback control law. Simulation results are presented for tracking the sinusoidal and constant reference input signal. Asymptotic trajectory control and the suppression of chaotic motion in spite of uncertainties in the system are accomplished.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.7
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• pp.927-934
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• 2012

This paper suggests a new fuzzy PID controller with variable parameters which improves the shortage of the fuzzy PID controller with fixed parameters suggested in [9]. The derivation procedure follows the general design procedure of the fuzzy logic controller, while the resultant control law is the form of the conventional PID controller. Therefore, the suggested controller has two advantages. One is that it has only four fuzzy linguistic rules and analytical form of control laws so that the real-time control system can be implemented based on low-price microprocessors. The other is that the PID control action can always be achieved with time-varying PID controller gains only by adjusting the input and output scalers at each sampling time.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.136-144
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• 1999

This paper deals with the fault detection problem in uncertain linear multivariable systems and its application. A robust fault detection method presented by Kim et a. (1998) for MIMO (Multi Input/Multi Output) systems has been adopted and applied to the twin rotor MIMO experimental setup using industrial DSP. The system identification problem is formulated for the twin rotor MIMO system and its parameters are estimated using experimental data. Based on the estimated parameters, some fault detection simulations are performed using the robust fault detection method, which shows that the preformance is satisfied.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.36-42
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• 1996

In this paper, we proposed a PID controller, which could control unknown plants using Artificial Neural Network(ANN) for auto-tuning of the PID parameters. In the proposed algorithm, the parameters of the controller were adjusted to reduce the error of the controlled plant. In this process, the sensitivity between input and output of the unknown plant was needed. So, in order to obtain this sensitivity, the ANN's learnig ability was used. Computer simualtions were performed for the regulation problems, and the results were compared with those of Ziegler-Nichols PID controller. As a result, it was shown that the proposed algorithm outperformed Ziegler-Nichols controller in rise time, overshoot, undershoot, and setting time.

• 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 Industrial Technology
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• v.31 no.A
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• pp.3-9
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• 2011

Simulation plays an important role for system analysis. In this study, a manufacturing system has been analyzed through computer simulation. We first briefly explain the considered system with prevailing problems. We then build a simulation model using ARENA simulation language. Based on two selected performance measures, material transporter load and hourly throughput, explicit system analyses have been performed. We addressed four parameters - variation of the processing time, number of raw material transporters, quality failure rate, and machine failures - as the input parameters affecting the output measures selected. We adopted Taguchi's orthogonal array in statistical experimental design and drew meaningful results from the analysis. The results given in the study may provide a good guidance for practical applications.