• 대한전기학회논문지
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• 제37권12호
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• pp.879-883
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• 1988

In this paper, self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in MIMO ARMA procss. This process is simlified as independent SISO ARMA processes having offset terma, which are considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the paramter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results consider well with the analysis in case of linear interconnection.

• 전력전자학회논문지
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• 제10권1호
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• pp.29-37
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• 2005

본 논문에서는 PI형태의 속도제어기를 장착한 고성능 유도전동기의 조건부 적분형 자동 튜닝 anti-windup 기법을 제안한다. 제안된 방법에서는 전동기 운전 조건에 대한 사전 정보 없이도 전동기 토오크 지령의 주파수 해석에 의해서 적분기 온/오프 시점이 결정된다. 따라서, 사용자는 anti-windup 동작을 위한 별도의 제어 상수를 설정하지 않아도 된다. 또한, 동작 조건이 변동하여도 과도 상태의 속도는 항상 최소한의 오버슈우트와 점착시간을 가지도록 동작한다. 본 기법은 속도 및 토오크 응답의 오버슈우트를 허용하지 않는 유도전동기 고성능 응용 분야에 유용하게 적용 될 수 있으며, 기본 개념은 화학 공정이나 산업용 로봇과 같은 일반 산업 응용 분야에도 확대 적용 가능하다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(1)
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• pp.312-315
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• 2004

This paper presents a tuning-free conditional integration anti-windup strategy for induction machine with Proportional-Integral (PI) type speed controller. The on/off condition of integral action is determined by the frequency domain analysis of machine torque command without a prior knowledge of set-point changes. There are no tuning parameters to be selected by users for anti-windup scheme. In addition, the dynamic performance of the proposed scheme assures a desired tracking response curve with minimal oscillation and settling time even in the change of operating conditions. This algorithm is useful in many high performance induction machine applications not to allow the oscillation and overshoot of speed/torque responses. The main idea can be extended to general applications such as chemical processes and industrial robots.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.295-298
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• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1242-1244
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• 1999

AVR parameter tuning for voltage control of power system generators has generally been done with the open-circuit model of the synchronous generator. When the generator is connected on-line and operating at rated load conditions, the AVR operates in an entirely different environment from the open-circuit conditions. This paper describes a new method for AVR parameter tuning using optimization technique with on-line linearized system model. As this method considers not only the on-line models but also the off-line open-circuit models, AVR parameters tuned by this method can give the sufficiently stable performance at the open-circuit commissioning phase and give the desired performance at the operating conditions. Also this method estimates the optimum parameters for desired performance indices that are chosen for satisfying requirements in some practical applications, the performance of the AVR can satisfy the various requirements.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.897-899
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• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.118-126
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• 2002

AVR parameter tuning for voltage control of generators has generally been done with the off-line open-circuit model of the synchronous generator. When the generator is connected on-line and operating with load the AVR operates in an entirely different environment from the open-circuit conditions. This paper describes a new method for AVR parameter tuning for on line conditions using SQP(Sequential Quadratic Programming) meshed with frequency response characteristics of linearized on-line system model. As the proposed method uses the un - line system model the tuned parameter sets show more optimal behavior in the on-line operating conditions. furthermore, as this method considers the performance indices that are needed for stable operation as constraints, AVR parameter sets that are tuned by this method could guarantee the stable performance, too.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.105-109
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• 2001

This paper discuss the real-time self-tuning learning control based on evolutionary computation, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• 대한기계학회논문집A
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• 제27권9호
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• pp.1463-1468
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• 2003

This paper presented the real-time self-tuning learning control based on evolutionary computation, which proves its superiority in finding of the optimal solution at the off-line learning method. The individuals of the populations are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations is proposed. It is possible to control the control object slightly varied as time changes. As the state value of the control object is generated, evolutionary strategy is applied each sampling time because the learning process of an estimation, selection, mutation is done in real-time. These algorithms can be applied; the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.