• Journal of Mechanical Science and Technology
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• v.15 no.10
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• pp.1356-1368
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• 2001

In this paper, the model reference adaptive control (MRAC) of a flexible structure is investigated. Any mechanically flexible structure is inherently distributed parameter in nature, so that its dynamics are described by a partial, rather than ordinary, differential equation. The MRAC problem is formulated as an initial value problem of coupled partial and ordinary differential equations in weak form. The well-posedness of the initial value problem is proved. The control law is derived by using the Lyapunov redesign method on an infinite dimensional filbert space. Uniform asymptotic stability of the closed loop system is established, and asymptotic tracking, i. e., convergence of the state-error to zero, is obtained. With an additional persistence of excitation condition for the reference model, parameter-error convergence to zero is also shown. Numerical simulations are provided.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.222-224
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller for a vector controlled induction motor drive. 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 model reference adaptive control(mAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.92-99
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• 1997

A model reference adaptive control(MRAC) theory is very useful for controlling a plant of which the parameters are unknown or vary during operation usint only input-output signal of plant. In this study, 2' nd order discreter time MRAC controller is designed for an electrohydraulic position control system which is represented with nonlinear mathematical model and the least square method is adopted for the para-meter adjustment law. This control algorthm is applied to the position control of electrohydraulic servosystem through computer simulation and the effect of the change of load, sampling time upon the performance following reference model and upon the performance of estimating plant parameters are examined.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.884-893
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• 1988

Adaptive controllers for linear unknown coefficient system, that is corrupted by disturbance, are designed by parameter adaptation model reference adaptive control(MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the convergence rate of the design, an indirect-suboptimal control law is derived. Proper compensation for the effects of time-varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.10
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• pp.733-739
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• 1988

Adaptive controllers for linear system whose nominal values of coefficients only are known, that is corrupted by disturbance, are designed by signal synthesis model reference adaptive control (MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the conrergence rate of the design, an indirect suboptimal control law is de rived using the Hamilton Jacobi Beellman equation. Proper compensaton for the effects of time varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.181-185
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• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). The drive is based on Mode1 Reference Adaptive System (MRAS) using state observer as a reference model fat flux estimation. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAS) with rotor flux linkages for the speed turning aignal at low speed range, two hysteresis controllers. The Proposed system is verified through simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.330-335
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• 1994

In this paper, adaprive control and sliding mode control are combined to implement the proposed adaptive sliding mode control(ASMC) algorithm which is new approach to the control of industrial robot manipulator with external disturbances and parameter uncertainties. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The contribution of this method is that the parameters of the sliding surface are replaced by time varying parameters whose are calculated by an adaptation algorithm, which forces the errors to follow the behavior of a reference error model. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2708-2715
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• 2012

This paper proposes a new sensorless speed control scheme of induction motor using Model Reference Adaptive Control and Direct Torque Control System. The Model Reference Adaptive Control System is based on the comparison between the outputs of Reference Model and Adjustable Model. The error between the estimated quantities obtained by the two models is used to drive a suitable adaptation mechanism which generates the estimated rotor speed for the Adjustable Model. And the Direct Torque Control scheme controls torque and flux by restricting the flux and torque errors within respective hysteresis bands, and motor torque and flux are controlled by the stator voltage space vector using optimum inverter switching table. The simulation results of proposed method indicate good speed responses from the low speed range to the high, and also show favorable characteristics of load operation.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.95-96
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• 1986

시스템을 입력과 출력값 만으로 제어하고자 할 경우에는, 플랜트의 파라메타를 추정하면서 제어해 나가야 할 것이다. 이러한 경우에는, 귀환제어나 최적제어 형태로는 여러가지 문제점이 발견되어서, 최근에 적응제어가 많이 연구되고 있다. 이에는 Gain-Scheduling 방법, Self-tuning regulator 방법 및 model reference adaptive control 방법이 있다. Gain-Scheduling 방법은 미지의 파라메타가 plant에 있을지라도, 이를 즉시 예측할 수 있을 경우 보조변수 추정을 통하여 이득을 조절하여 시스템을 안정시키는 것이고, self tuning regulator는 보조변수를 직접 조정하여 시스템을 제어한다. 또 model reference adaptive control 방법은 기준모델을 정하여, 이에 따라 관측기 등을 통하여, 플랜트의 파라메타를 추정 제어해 나가는 것이다. 이때 기준 모델의 출력과 플랜트 출력사이의 오차를 어떻게 할 것인가? 추정되는 파라메타와 오차와의 대수관계 및 차수 등, 그 한계 해석이 최근의 MRAC 설계연구에 큰 과제가 되어 왔다. 이에 본 연구에서는 신호합성 및 해석에 뛰어난 기능이 있는 Walsh 함수를 이용하여, 간단한 Micro computer의 도움으로, 오차 함수를 합성하고, 미지의 파라메타를 추정하여, 시스템의 adaptive filter설계에의 가능성에 대하여 연구하고자 한다. 또 이를 실제 예를 들어 고찰하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.5
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• pp.258-265
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• 1985

A design method for a single-input single-output discrete time model reference adaptive system is described in this paper. By using the state-variable filters into inputs and outputs in reference model and unknown system, a simple adaptive structure which use all accessible signals can be constructed. Some papers for the adaptive shstem is which thw relative degree of unknown system have one or two have been reported, but the resulting adaptive system are intricate in structures and the design theories for the model reference adaptive system are not generalized. In this paper, for having two or more relative degrees, it has been verified that an adaptive scheme can be obtained by introducing a simple linear filter.