• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.307-308
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• 2007

In general, most physical systems are complex, highly non-linearity, affected by disturbance, incomplete knowledge, and even interactive change with the operating points. To solve this problem, the research of modem control theory and controller is proceeding. Before appling the proposed controller to the real system, however, it needs an apparatus which can verify the proposed controller for being not damaged the plant. In this paper, therefore, a RCGA-based PI-type state feedback controller using reduced-order observer is implemented and applied to the seesaw system and a series of simulation are carried out to verify the effectiveness of the control system.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.65-72
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• 2001

Power system stabilizer act efficiently to damp the electromechanical oscillations in interconnected power systems. This paper presents an algorithm for the optimal parameter selection of a power system stabilizer in two-area power systems with a series HVDC link. This method is one of the classical techniques by allocating properly pole-zero positions to fit as closely as desired the ideal phase lead between the voltage reference and the generator electrical power and by changing the gain to produce a necessary damping torque over the matched frequency range. Control of HVDC converter and inverter are used a constant current loop. Proper parameters of PI controllers are obtain based on the Root-locus technique in other to have sufficient speed and stability margin to cope with charging reference values and disturbance. The small signal stability arid transient stability studies using the PSS parameters obtained from this method show that a natural oscillation frequency of the studycase system is adequately damped. Also the simulation results using the HVDC converter and inverter parameters obtained from this proposed method show proper current control characteristics. The simulation used in the paper was performed by the Power System Toolbox software program based on MATLAB.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1207-1214
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• 2017

In the case of frequent braking, when driving downhill or long distance, conventional brakes using friction are problematic in braking safety due to brake rupture and fading phenomenon. Therefore auxiliary brakes is essential for heavy vehicles. And several research has been actively conducted to improve energy efficiency by regenerating mechanical energy into electric energy when the vehicles brake. In this paper, a voltage control method is utilized to recover the electric energy generated in the electromagnetic retarder instead of the eddy current. To regenerate the braking energy into the electrical energy, a resonant L-C circuit is configured in the retarder. The retarder can be modeled as self-excited induction generator due to its operating principle. The driving conditions according to the retarder's parameters are made into 3-D maps. Also, the voltage of the resonant circuit changing depending on the driving pulse applied to the FET was analyzed. For the control of this voltage, we proposed an algorithm using the PI controller. The controlled voltage is converted by a 3-phase AC/DC converter and then charged to a battery inside the heavy vehicles through a DC/DC converter. Electromagnetic retarder and its controller are validated using Matlab Simulink. We also demonstrate the voltage controller through the actual M-G set experiment.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.61-67
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up. nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.282-289
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• 2005

This paper proposes a fuzzy neural network controller based on the vector control for interior permanent magnet synchronous motor(IPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability This paper does not oかy presents speed control of IPMSM using neuro-fuzzy control(NFC) but also speed estimation 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 error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. Thus, it is presented the theoretical analysis as well as the analysis results to verify the effectiveness of the proposed method in this paper.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.689-697
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• 2005

In this paper, an application of a decentralized $H_{\infty}$ controller(DHC) to multiple controlled-permanent magnet(CMAG) magnetic levitation(Maglev) systems is presented. The designed DHC using two Riccati equations iteratively has simpler structure and needs less computational loads than conventional centralized $H_{\infty}$ controller. A target plant is a hybrid-type CMAG system with permanent magnet and coil, and its mathematical model is firstly derived to design the DHC. To implement the designed algorithm, a real Maglev vehicle system including digital controller, chopper, sensor, etc., is manufactured. To compare the performances of the DHC method with an observer-based state feedback control(OSFC), the input tracking and disturbance rejection characteristics are experimentally tested. As performance indices(PI), integral of squared error(ISE), integral of absolute error(IAE), integral of time multiplied by absolute error(ITAE) and integral of time multiplied by squared error(ITSE) are used. From the experimental results, it can be seen that the input tracking and disturbance rejection performances of the DHC are better than those of the conventional controller.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.516-518
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• 1999

This paper presents an feed-forward neural network design instead PI controller for the speed control of an Induction Motor. The design employs the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE). Emulator identifies the motor by simulating the input and output map. In order to update the weights of the Controller. Emulator supplies the error path to the output stage of the controller using backpropagation algorithm. and then Controller produces an adequate output to the system due to neural networks learning capability. Therefore it becomes adjustable to the system with changing characteristics caused by a load. The speed control based on neural networks for induction motor is implemented by a vector controlled induction motor. The simulation results demonstrate that actual motor speed with neural network system well follows the reference speed minimizing the error and is available to implement on the vector control theory.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.278-280
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• 1999

This paper proposes controlling of temperature in an oven by using 4 bits Integral - Cycle Binary Rate Modulation (IBRM) method and ac line with frequency 50 Hz. Microcontroller MCS-51 controls IBRM according to Proportional Integral controller (PI) function. Discrete signals are used in the system modeled by using Ziegler Nichols principle for analyzing the stability before designing the system. This procedure makes it easy to investigate system response. The system is implemented by 4 bits digital circuit which gives 320 patterns of ac signal fur controlling the generation of energy for 3,000 watts thermal coil every 20 ms of each cycle. We divide scan time (Ts$\sub$n/) in to 20 intervals, 1 ms interval is selected to generate 16 patterns IBRM. Because of this method gives the ripple lower than 2% it generates less noise fur system. Moreover, we can consider whole system from the time model of control procedure and IBRM algorithm at 40-200$^{\circ}C$ with ${\pm}$ 1$^{\circ}C$ error in the 1 cubic meter oven.

• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.245-250
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• 2009

We propose a digital holographic interference analysis method based on a 2-frame phase-shifting technique for measuring an optical mirror surface. The technique using 2-frame phase-shifting digital interferometry is more efficient than multi-frame phase-shifting techniques because the 2-frame method has the advantage of a reduced number of interferograms, and then takes less time to acquire the wanted topography information from interferograms. In this measurement system, 2-frame phase-shifting digital interferograms are acquired by moving the reference flat mirror surface, which is attached to a piezoelectric transducer, with phase step of 0 or $\pi$/2 in the reference beam path. The measurements are recorded on a CCD detector. The optical interferometry is designed on the basis of polarization characteristics of a polarizing beam splitter. Therefore the noise from outside turbulence can be decreased. The proposed 2-frame algorithm uses the relative phase difference of the neighbor pixels. The experiment has been carried out on an optical mirror which flatness is less than $\lambda$/4. The measurement of the optical mirror surface topography using 2-frame phase-shifting interferometry shows that the peak-to-peak value is calculated to be about $0.1779{\mu}m$, the root-mean-square value is about $0.034{\mu}m$. Thus, the proposed method is expected to be used in nondestructive testing of optical components.