• 한국통신학회논문지
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• 제18권7호
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• pp.1009-1017
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• 1993

본 논문에서는 유계된 파라메터섭등과 외란및 측정 잡음이 존재하는 프로세스에서 점근적으로 제어기의 기준입력에 추종하고 전체 안정도를 보장하는 강건한 파라메터 적응서보 제어기를 설계하였다. 이 제어기는 평가함수를 최소화하면서 제어기 파라메터를 추정하는 구조를 갖는다. DC서보의 속도위치와 위치제어를 통해서 섭동과 외란에 대한 최소분산 제어기 파라메터 추정의 강건함을 적용해 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.420-425
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• 1996

In this paper a robust speed controller for an induction motor is proposed. The speed controller consists or a fuzzy sliding adaptive controller(FSAC) and a sliding mode torque observer(SMTO). FSAC removes the problem or oscillations caused by discontinuous inputs of the sliding mode controller. The controller also provides robust characteristics against parameter and sampling time variations. Although, however, the performance of FSAC is better than PI controller and fuzzy controller in robustness, it generates the problem of slow response time. To alleviate this problem, a compensator, which performs feedforward control using torque signals produced by SMTO, is added. The simulation and hardware implementation results show that the proposed system is robust to the load disturbance, parameter variations, and measurement noises.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.262-266
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• 1995

This paper presents a new adaptive-neuro control scheme to control the velocity and position of SCARA robot with parameter uncertainties. The adaptive control of linear system found wiedly in many areas of control application. While techniques for the adaptive control of linear systems have been well-established in the literature, there are a few corresponding techniques for nonlinear systems. In this paper an attempt is made to present a newcontrol scheme for theadaptive control of ponlinear robot based on a feedforward neural network. The proposed approach incorporates a neuro controller used within a reinforcement learning framework, which reduces the problem to one of learning a stochastic approximation of an unknown average error surface Emphasis is focused on the fact that the adaptive-neuro controoler dose not need any input/output information about the controlled system. The simulation result illustrates the effectiveness of the proposed adaptive-neuro control scheme.

• 전기학회논문지
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• 제60권5호
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• pp.977-983
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• 2011

This paper proposes a new adaptive speed controller to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed adaptive regulator does not require any information on the motor parameter and load torque values, so it is very insensitive to model parameter and load torque variations. Also, the stability of the proposed adaptive control system is proven. To validate the robustness of the proposed adaptive speed controller, both simulation and experimental results are provided under motor parameter and load torque variations. It is clearly demonstrated that the proposed adaptive regulator can accurately control the speed of permanent magnet synchronous motors.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.4-9
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• 1999

A new control method for precision robust position control of a brushless DC (BLDC) motor using asymptotically stable adaptive load torque observer is presented in the paper. Precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method Recently, many of these drive systems use BLDC motors to avoid backlashe. However, the disadvantages of the motor are high cost and complex control because of nonlinear characteristics. Also, the load torque disturbance directly affects the motor shaft. The application of the load torque observer is published in [1] using fixed gain. However, the motor flux linkage is not exactly known for a load torque observer. There is the problem of uncertainty to obtain very high precision position control. Therefore a model reference adaptive observer is considered to overcome the problem of unknown parameter and torque disturbance in this paper. The system stability analysis is carried out using Lyapunov stability theorem. As a result, asymptotically stable observe gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current which gives fast response. The experimenta results are presented in the paper.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.418-423
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• 1992

In this paper, a model reference adaptive control algorithm is applied to the design of the normal acceleration controller for missiles with nonminimum-phase characteristics. The method used in this paper is due to Ohkubo. In this scheme, a feedforward compensator is designed first so that the extended system becomes minimum-phase and after that an adaptive control algorithms is designed for the extended system. The feedforwrd compensator is obtained by solving the robust stabilization problem. It is shown that the performance of the designed controller is satisfied via computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.872-877
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• 1990

Robustness of a model refernece direct adaptive pole placement control for not necessarily minimum phase systems is studied subject to unmodeled dynamics and bounded disturbances. The adaptive control scheme involves two estimators for the system and the controller parameter estimation, respectively. The robustness is obtaind under some weak assumptions and by using both a normalized least-squares algorithm with dead zone and an appropriate nonlinear feedback.

• Nuclear Engineering and Technology
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• 제25권1호
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• pp.110-124
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• 1993

적응 비례-적분-추정 (PIF) gain 및 가변구조 제어기를 사용하는 비선형 모델에 의한 하이브리드 제어방법 (NHC)이 개발되었다. 이 제어기는 모델의 불확실성에 대해 robust한 성질을 가지며 단일 입-출력 비선형 시스템의 추적제어 (tracking control)에 응용된다. 이 방법의 특징은 제어기가 각각 특정 역할을 수행하는 4개 부분으로 구성되는 것이다. 즉, 적응 P-I-F 및 가변구조 제어기로 구성된다. Lyapunov의 제 2방법으로 결정된 적응 PIF gain에 의한 제어성능 확보 및 모델의 불확실도를 평가하여 피이드백 함으로써 모델의 불확실성에 대해 robust한 제어기를 구성하였다. 가변구조 제어기는 PIF gain이 적절히 결정되지 않은 상태인 초기의 오차증가를 제어하기 위해 도입되었다. 새로 개발된 NHC방법을 원자로의 출력변동 제어에 응용한 결과 기존의 모델을 이용한 제어방법 (model-based controller)들에 비해 제어성능이 크게 개선되었다.

• 제어로봇시스템학회논문지
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• 제7권7호
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• pp.605-613
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• 2001

In this paper, we design a robust adaptive controller for a nonlinear system with uncertainties to be rejected via disturbance adaptation law. The nonlinear system considered has unknown nonlinear functions being influenced by external disturbance. The upper bound of unknown nonlinear functions at each time is estimated by using a disturbance adaptation law. The estimated nonlinear functions are used to design a stabilizing function a control input. Tuning function is used to estimates unknown system parameter without overparametrization. A set-point regulation error converges to a residual set close to zero asymptotically. The effectiveness of the proposed controller is investigated by computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.332-334
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• 1994

This paper proposes a robust active noise control (ANC) system. The system constructs filter with a standard model. An adaptive litter, connected to the system in parallel, compensates the modeling error. When the adaptive filter does not work, the proposed system is robust while the conventional system loses the noise control capability. But proposed ANC system shows that the performance is comparable with that of the conventional ANC system under normal conditions.