• 한국산학기술학회논문지
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• 제17권2호
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• pp.697-702
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• 2016

매입형 영구자석 동기전동기의 원활한 제어를 위해서는 전동기의 상수인 고정자 저항이나 각종 인덕턴스의 값, 그리고 쇄교 자속의 값 등을 정확하게 알아야 한다. 그러나 이러한 상수들은 전동기 운행에 따른 전동기 온도의 상승이나 각 작동점 등의 변화에 따라 계속적으로 변하기 때문에 이들의 값을 정확하게 추정하는 것은 매우 어렵다. 이러한 문제점을 극복하기 위해서 실시간으로 상수의 값을 추정하는 기법이 필요한데 본 논문에서는 MRAS(Model Reference Adaptive System) 기법을 이용한 상수의 추정 및 적응제어 기법을 제시한다. 시스템의 관계식이 이들 상수에 대해 비선형으로 구성되어 있어 일반적인 제어기법을 적용하는데 문제가 있어 일부 논문에서는 상수의 일부를 안다고 가정하였지만 본 논문에서는 이러한 가정 없이 모든 상수를 추정하는 제어기법을 제시하고 적응제어 기법의 수렴성을 입증하였다. 제시하는 알고리즘의 우수성은 시뮬레이션을 통해 입증하도록 한다.

• 한국공작기계학회논문집
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• 제12권6호
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• pp.77-83
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• 2003

This paper deals with a position control problem of a hydraulic proportional position control system using a nonlinear friction compensation control. As nonlinear friction, stiction and coulomb friction forces are considered and modeled as deadzone and external disturbance respectively. In order to compensate this nonlinearities, we designed the controller which is the adaptive friction compensator using discrete time Model Reference Adaptive Control method in this paper. Digital Signal Processing board is employed for data acquisition and manipulation. The experimental results show that response is slow and steady-state error cannot be compensated properly without friction compensation but this compensator is effective to obtain fast response and good steady-state response.

• 전기전자학회논문지
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• 제1권1호
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• pp.55-63
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• 1997

본 논문의 목적은 유도 전동기의 속도 센서 없는 견실한 벡터 제어의 구현에 있다. 이를 위해 MRAS(Model Reference Adaptive System)를 사용하여 유도 전동기의 속도를 추정하였고 파라미터 변동에 견실한 두 개의 회전자 자속 관측기를 설계하여 MRAS 속도 추정기에 기준 모델과 추정 모델로 사용하였다. MRAS에 근거를 둔 전체 제어 기법은 2.2kW 유도 전동기의 벡터 제어 드라이브를 사용하여 실현되었으며, 본 논문에서 제한한 속도 센서 없는 벡터 제어 기법이 기존의 속도 센서 없는 제어 기법에 비해 보다 안정하고 견실함을 증명하였다.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

• 제어로봇시스템학회논문지
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• 제12권12호
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• pp.1220-1230
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• 2006

In this paper, we propose a flew technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• 동력기계공학회지
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• 제21권4호
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• pp.42-50
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• 2017

A velocity controller using a modified model reference adaptive controller (M-MRAC) and a projection operator for a fish sorting belt conveyor system with uncertainty parameters, input saturation and bounded disturbances is proposed in this paper. To improve the tracking performance and robustness of the proposed controller in the presence of bounded disturbances, the followings are done. Firstly, the reference model for the conventional model reference adaptive controller (CMRAC) is replaced by a modified reference model for a M-MRAC to reduce unexpected high frequency oscillation in control input signal when the adaptation rate is increased. Secondly, estimated parameters in an adaptive law are varied smoothly under bounded external disturbances and a projection operator is utilized in an adaptive law for the proposed M-MRAC controller to be robust. Thirdly, an auxiliary error vector is introduced for compensating the error dynamics of the system when the saturation input occurs. Finally, the experimental results are shown to verify the better effectiveness and performance of the proposed controller under the bounded disturbance and saturated input than that of a CMRAC.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권9호
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• 대한전기학회논문지
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• 제32권6호
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• pp.219-224
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• 1983

The problem of model reference adaptive control for the discrete time system is considered and the global stability of the overall system is shown. It extends the results of Kreisselmeier's to more general reference models and the method presented here makes the output error and controller parameter error converge to zero. The scheme presented in this paper is simulated and the simulation gives the expected results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.993-998
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• 1988

Adaptive control system has evolved as an attempt to avoid degradation of the dynamic performance of a control system when environmental variations occurs. While the feedback control system is oriented toward the elimination of the effect of state perturbations, the adaptive control system is oriented toward the elimination of the effect of structural perturbation, upon the performances of the control system. The model reference adaptive controller is utilized in velocity loop controller for positioning and tracking is designed based on the linear decoupled dynamics.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.129-132
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• 2001

In this paper, in order to control uncertain missile autopilot, an adaptive fuzzy control(AEC) scheme via parallel distributed compensation(PDC) is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy model. Moreover adaptive law is designed so that the plant output tracks the stable reference model(SRM), From the simulations results, we can conclude that the suggested scheme can effectively solve the control problems of uncertain missile systems based on T-S fuzzy model.