• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.1408-1410
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• 2000

The regulation performances needs high control gain in novel output feedback controller but high control gain is decreased relative stability of the total system. Thus, this paper proposed neural network controller(NNC) for output feedback controller. In this scheme, output feedback controller are guarantee global stability and NNC are controller steady-state error and defined optimal control law. And we demonstrated this scheme by simulations.

• 전기의세계
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• 제25권5호
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• pp.70-74
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• 1976

In this paper, the problem of controlling deterministic contimuous linear system with a slightly modified quadratic performance criteria is studied. When the number of out put variables is much lesser then that of state variables, either the controller becomes complex or the performance measure becomes much higher with only output feedback. So the design philosphy treated in this paper lies in finding a compromising point between the controller complexity and the performance measure. thd controller is composed of stasic plus dynamic compensator with order equal to the mtmber of output variables. Several unknowns are unknown parameters are bundled into one, and using Pontryagin's minimum principle, conditions and formula for optimum control are induced which are different from that of Kalman optimal regulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.501-503
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• 1999

In this paper, the design method of a hybrid fuzzy controller with an optimal auto-tuning method is proposed. The conventional PID controller becomes so sensitive to the control environments and the change of parameters that the efficiency of its utility for the complex and nonlinear plant has been questioned in transient state. In this paper, first, a hybrid fuzzy logic controller(HFLC) is proposed. The control input of the system in the HFLC is a convex combination by a fuzzy variable of the FLC's output in transient state and the PID's output in steady state. Second, a powerful auto-tuning algorithm is presented to automatically improve the Performance of controller, utilizing the improved complex method and the genetic algorithm. The algorithm estimates automatically the optimal values of scaling factors and PID coefficients. Controllers are applied to the plants with time-delay and the DC servo motor Computer simulations are conducted at the step input and the system performances are evaluated in the ITAE.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.485-485
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• 2000

A design method of model following control system using neural networks is proposed. An unknown nonlinear single-input single-output plant is identified using a multilayer neural networks. A linear controller is designed fer the linear approximation model obtained by linearinzing the identification model. The identification model is also used as a plant emulator to obtain the prediction error. Deficient servo performance due to controlling nonlinear plant with only linear controller is mended by adjusting the linear controller output using the prediction output and the parameters of the identification model. An optimal preview controller is adopted as the linear controller by reason of having good servo performance lowering the peak of control input. Validity of proposed method is illustrated through a numerical simulation.

• 한국지능시스템학회논문지
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• 제7권2호
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• pp.52-65
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• 1997

이 논문은 전력계통의 부하주파수 제어를 위한 자기조정 퍼지제어기의 설계기법을 제시한다. 제안된 퍼지제어기의 파라미터 자기조정 알고리즘은 퍼지제어기의 추론값과 최적 제어기의 출력값들 사이의 오차를 감소시키는 네개의 방향 벡터를 사용하는 구배법에 기초를 둔다. 최적 제어기로부터 얻어진 입,출력 데이터쌍을 사용하여, 퍼지추론 룰의 전건부와 후건부에서의 파라미터들은 제안된 구배법에 으해 자동조정되고 학습되어진다. 시뮬레이션 결과, 제안된 퍼지제어기가 종래의 제어기보다 우수한 제어성능을 보임을 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권11호
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.471-476
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• 1993

In this paper we proposed the digital implementation of an $H^{\infty}$-optimal controller using lifting technique and $H^{\infty}$-control theory. The discrete controller is obtained through iterative adjustment of sampling time and weighting function, which can ber performed by computing the L$_{2}$-induced input to output norm of the sampled-data system with bandlimited exogenous input. The resulting sampled-data bandlimited exogenous input. The resulting sampled-data system is stable and the performance including inter-sampling behaviour of the hybrid system can be also optimized.d.

• 전기학회논문지
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• 제60권2호
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• pp.407-415
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• 2011

In this study, we propose the design of optimized fuzzy controller for the rotary inverted pendulum system by using differential evolution algorithm. The structure of the differential evolution algorithm has a simple structure and its convergence to optimal values is superb in comparison to other optimization algorithms. Also the differential evolution algorithm is easier to use because it have simpler mathematical operators and have much less computational time when compared with other optimization algorithms. The rotary inverted pendulum system is nonlinear and has a unstable motion. The objective is to control the position of the rotating arm and to make the pendulum to maintain the unstable equilibrium point at vertical position. The output performance of the proposed fuzzy controller is considered from the viewpoint of performance criteria such as overshoot, steady-state error, and settling time through simulation and practical experiment. From the result of both simulation and practical experiment, we evaluate and analyze the performance of the proposed optimal fuzzy controller from the comparison between PGAs and differential evolution algorithms. Also we show the superiority of the output performance as well as the characteristic of differential evolution algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.192-194
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• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.

• 한국항공우주학회지
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• 제32권8호
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• pp.109-117
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• 2004

항공기 조종면을 이용한 돌풍하중 완화기술에 대한 연구를 수행하였다 조종면 제어기를 포함하는 서보 공탄성 모델을 구성하였으며, 이에 대한 연속돌풍 응답해석을 수행하여 MSC/NASTRAN을 이용한 해석결과와 비교하여 시보 공탄성 모델을 검증하였다. 조종면 제어기 설계에는 출력 피드백을 이용한 최적 제어기법을 사용하였으며, 설계된 제어기에 대한 수치 시뮬레이션을 수행하여 돌풍하중 완화효과를 검증하였다.