• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2000년도 춘계학술대회
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• pp.41-41
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• 2000

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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• pp.2139-2142
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• 1997

The most important thing in vector control scheme is the knowledge of accurate electrical motor parameters. These parameters can computed by conventional motor test, such as no-load and locked rotor tests. However, the values from these tests are different from actual motor parameters, and the adjustment process of the parameters is time consuming. This paper presents an auto-tuning method for vector control of induction motor. The tuning algorithm is based on the rotor flux behavior of the induction motor for stepwise torque current command. The transient terminal voltage caused by the undesirable variation of the rotor flux is used for tuning the slip gain $K_5$ defined as the inverse of the rotor time constant. The electrical parameters of induction motor can also calculated by this method. The presented method is evaluated through the computer simulations.

• 대한기계학회논문집A
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• 제20권10호
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• pp.3038-3047
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• 1996

In telerobot systems, visual servoing of a task object for a slave arm with an eye-in-hand has drawn an interesting attention. As such a task ingenerally conducted in an unstructured environment, it is very difficult to define the inverse feature Jacobian matrix. To overcome this difficulty, this paper proposes an auto-tuning fuzzy rule-based visual servo algorithm. In this algorithm, a visual servo controller composed of fuzzy rules, receives feature errors as inputs and generates the change of have position as outputs. The fuzzy rules are tuned by using steepest gradient method of the cost function, which is defined as a quadratic function of feature errors. Since the fuzzy rules are tuned automatically, this method can be applied to the visual servoing of a slave arm in real time. The effctiveness of the proposed algorithm is verified through a series of simulations and experiments. The results show that through the learning procedure, the slave arm and track object in real time with reasonable accuracy.

• 대한전기학회논문지:전력기술부문A
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• 제48권1호
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• pp.36-43
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• 1999

This paper proposes a new hybrid genetic algorithm for auto-tuning fuzzy controllers improving the performance. In general, fuzzy controllers use pre-determined moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a hybrid genetic algorithm. The object of the proposed algorithm is to promote search efficiency by the hybrid optimization technique. The proposed hybrid genetic algorithm is based on both the standard genetic algorithm and a modified gradient method. If a maximum point is not be changed around an optimal value at the end of performance during given generation, the hybrid genetic algorithm searches for an optimal value using the the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algoritms. Simulation results verify the validity of the presented method.

• 전자공학회논문지B
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• 제32B권8호
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• pp.1119-1126
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• 1995

The construction of rule-base for a nonlinear time-varying system, becomes much more complicated because of model uncertainty and parameter variations. Furthemore, FLC does not have an ability of adjusting rule- base in responding to some sudden changes of control environments. To cope with these problems, an auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), which is known to be very effective in the optimization problem, will be proposed. The tuning of the proposed system is performed by two tuning processes(the course tuning process and the fine tuning/adaptive learning process). The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• 한국조명전기설비학회지:조명전기설비
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• 제7권4호
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• pp.42-50
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• 1993

본 연구에서는 자동동조 퍼지 PID 제어 앨고리즘을 사용하여 유도전동기 구동방법을 제안하였다. 퍼지제어에서는 수학적인 모델링이 없이 경험적인 정보를 이용하면 제어가 가능하며 퍼지룩업 테이블을 적절히 이용하면 실시간 제어도 가능한 것이 특징이라 볼 수 있다. 또한, 퍼지규칙을 몇 개의 영역으로 구획하여 시스템의 변화가 발생되고, 또 파라미터의 변화가 유도 전동기 구동 특성에 크게 영향을 주는 것을 감안, 본 시스템의 고성능, 고정도제어를 위하여 퍼지 앨고리즘을 적용하여 파라미터가 자동동조 기능을 갖는 유도전동기의 구동 시스템을 설계, 제작하였으며 그 특성을 기존의 PID 제어방식과 비교하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.423-426
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• 2005

In this paper, we proposed a PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.847-852
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• 1993

In this paper, we present a recursive algorithm for the auto-tuning of PID controllers by optimizing a GPC criterion. Also, we develop an intelligent PID controller by combination of a recursive algorithm together with a supervisor, that allows to adjust the main controller parameters (prediction horizon, control weighting, sample time etc.) using some simple rules which is mainly built up through relay tuning experiments. The intelligent PID controller has been implemented successfully on an IBM PC/AT and some simulation results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.123-128
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• 1992

This paper presents an autotuning algorithm of scaling factor in order to improve system performance. We define the scaling factor of fuzzy controller as a function of error and error change. This function is tuned by the output of performance evaluation level utilizing the error of overshoot and rising time. Simulation results show that the proposed algorithm has good tuning performance for a system with parameter change.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2702-2704
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• 2001

In this Letter, we propose a comprehensive design methodology of hybri'd Fuzzy controllers (HFC). The HFC comes as a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm) and an auto-tuning algorithm. The tuning of the scaling factors of the HFC is an essential component of the entire optimization process. A numerical study is presented and a detailed comparative analysis is also included.