• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.215-218
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• 2000

The windup phenomenon appears and degrades control performance when a controller with integrating action is used and the plant input is limited. An anti-windup integral -proportional(IP) controller is proposed for the variable-speed motor drives and it is experimentally applied to the speed control of a vector-controlled induction motor driven by a pulse width modulated (PWM) voltage source inverter(VSI). Although the operating conditions like motor load and speed command is changed under the limited plant input it is experimentally verified that the speed response has much improved performance such as no overshoot and fast settling time and the maximum plant input is also effectively utilized.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권10호
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• pp.625-633
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• 2004

This paper proposed a boost input type single stage resonant power supply for driving magnetron device. The proposed power supply can control both input power factor and output power at the same time. Also, because ZVS is achieved using the resonance between leakage inductance and resonant capacitance, switching losses are drastically reduced. To prevent breakdown or moding phenomenon of the magnetron due to excessive starting voltage, variable frequency ignition method is also proposed. Experimental results for the prototype power supply are presented and discussed to verify the validity of the proposed power supply.

• 한국통신학회논문지
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• 제21권11호
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• pp.3001-3011
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• 1996

In this paper, using DBNN algorithm which is used in the binary pattern classification or speech signal processing the digital DBNN circuit is designed having the variable expansion depending the size of input data and pattern type. The processing elemen(PE) of the proposed network consists of the synapse and MAXNET circuits for the similarity measurement between reference and input pattern. Global MAXNET selects the global winner among the local winners which is selected in each PE. Through the several simultions, and thus each PE and global MAXNET search the reference pattern that was the most simlar to input pattern for the discord of the pattern.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.404-407
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• 1992

In this thesis, the algorithm of Fuzzy Logic Control(FLC) is applied to the Nonlinear system to implement a system response. Proportional-Integral-Derivative(PID) controller is also used to control the various systems. Look-up table is applied to decide the control input, and the other look-up table is added for saving memories and inference time. Generally, FLC input variables are error(E) and error derivative($\Delta$E). In this algorithm. another Input variable error's second derivative($\Delta^2$E) is added for Robust Fine control.

• 동력기계공학회지
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• 제3권2호
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• pp.34-41
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• 1999

This paper identifies a linear combustion model of Refuse Incineration Plant(RIP) which characterizes its combustion dynamics, where the proposed model has thirteen-inputs and one-output. The structure of the RIP model is given as an ARX model which obtained from the theoretical analysis. And then, some unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. In result, it is shown that the proposed model well approximates the input-output combustion characteristics riven by experimental data sets.

• 전자공학회논문지B
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• 제30B권5호
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• 한국지능시스템학회논문지
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• 제9권6호
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• International Journal of Korean Welding Society
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• 제3권2호
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Electrical Engineering and information Science
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• 제2권4호
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• pp.53-58
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• 1997

In this paper, the power system stabilizer(PSS) using the sliding mode observer-model following(SMO-MF) with closed-loop feedback (CLF) for single machine system is extended to multimachine system. This a multimachine SMO-MF PSS for unmeasureable plant state variable is obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). And the estimated control input for unmeasurable plant sate variables is derived by Lyapunov's second method to determine a control input that keeps the system stable. Time domain simulation results for the torque angle and for the angular velocity show that the proposed multimachine SMO-MF PSS including CLF for unmeasurable plant sate variables is able to damp out the low frequency oscillation and to achieve asymptotic tracking error between the reference model state at different initial conditions and at step input.

• Journal of Welding and Joining
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• 제18권5호
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.