• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2052-2054
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• 2003

본 논문에서는 혼돈 비선형 시스템의 지능 제어를 위해 간접 적응 제어 기법에 기반한 웨이블릿 신경 회로망 제어기 설계 방법을 제안한다. 제어기 성능에 큰 영향을 미칠 수 있는 웨이블릿 신경 회로망 구조의 파라미터 동정은 본질적으로 강인하고 전역 최적해에 근사한 값을 결정할 수 있는 유전 알고리듬을 사용한다. 본 논문에서 제안한 제어 방법은 유전 알고리듬을 이용한 혼돈 비선형 시스템의 오프라인 동정 모델 및 기준 신호와 플랜트 출력으로 정의되는 제어 오차를 이용하여 원하는 제어 입력을 생성한다. 한편 본 논문에서 제안한 웨이블릿 신경 회로망 제어기를 대표적인 연속 시간 혼돈 비선형 시스템인 Duffing 시스템에 적용하여 설계된 제어기의 효율성 및 우수성을 검증하고자 한다.

• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.250-258
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• 1999

This paper presents a decentralized adaptive controller design for a Magnetically Levitated Fine Manipulator to follow the given trajectory as close as possible in spite of coupling effects between motion axes(degree of freedoms or subsystems). The present controller consists of two parts: the model reference controls based on known subsystems and the local adaptive controls. The former stabilizes the motion of the manipulator so as to follow that of the reference model. The latter reduces tracking errors due to coupling disturbances by adjusting the local gains to such levels that override interactions and assure the stability of the overall system. Through several experimental results, it has been shown that the decentralized adaptive control scheme has better tracking performances comparing to the PID controller case as well as good disturbance(coupling) rejection property.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1073-1076
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• 1991

This paper presents a robust model reference adaptive controller for continuous-time single-input single-output linear time-invariant systems which are subjected to output-dependent disturbances as well as bounded external disturbances. In the derived controller form, an additional output error feedback term is included to over-ride the destabilizing effects by the output-dependent disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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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.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.211-212
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• 2015

본 논문에서는 MRAS(Model Reference Adaptive System)을 이용한 유도 전동기의 회전자 저항을 추정하는 방법을 제안하였다. 슬립 계산은 회전자 저항 값과 연관되어 있기 때문에, 잘못된 회전자 저항 값 정보는 벡터제어의 동특성을 저하시킬 수 있다. 따라서 회전자 저항 값을 정확히 측정 또는 추정이 매우 중요하다. 본 논문에서는 회전자 자속의 크기 기반의 MRAS를 바탕으로 회전자 자속 전압 모델을 기준 모델로 구성하고 회전자 자속 전류 모델을 적응 모델로 구성하는 방법을 제안하였다. 제안한 방법은 두 모델 사이의 오차 신호를 영으로 수렴하도록 적응 메커니즘을 구성하여 회전자 저항 값을 추정한다. 본 논문에서는 시뮬레이션을 통하여 제안된 방법의 타당성을 검증하였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.597-602
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• 1987

In this paper, an adaptive observe based upon the exponentially weighted least-squares method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. A method of selecting the state variable filter is proposed. In this scheme, all the past data are weithted exponentially with the weighting coefficient.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.119-123
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• 2007

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS(Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Control algorithm that propose whole system through MATLAB SIMULINK because do modelling simulation result are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor. Therefore we hope to be extended in industrial application.

• Journal of Drive and Control
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• v.9 no.3
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• pp.1-7
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• 2012

This paper deals with the issue of model reference adaptive control strategy to control the injection molding machine. Prior to controller design, a pair of transfer functions are derived for the injection and dwelling process based on mathematical models of components. As external disturbances to examine the robustness of the proposed controller, nozzle clogging and contraction of molded objects are considered and realized by proportional valve. The overall simulation system, consisting of hydraulic components, controller and sensors, is implemented using the components of commercial software SimulationX. The simulation results confirm the proposed scheme's efficiency and robustness.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.34-43
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• 1990

An improved parameter adaptation and control law for robot manipulator are proposed based on a linearized parametric system equation and augmented error vectors. In view of the modeling error and parasitics with small time constants which inevitably introduced during modelling process, their effects on the robustness of the system performance are reviewed and as an conutermearsure, adaptation mechanism with low pass filter is proposed. Proposed parameter adaptation and control low assure the stability of the robot manipulator in the large without further assumption. Computer simulation shows its effectiveness of the proposed adaptation mechanism to improve the robustness of the system in presence of the parasitics in the system and superior performance for high speed operations make it an attractive option in application of the adaptive control field for robot manipulator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.88-95
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• 2005

This paper presents a design scheme of model reference adaptive control incorporating a Neural Network for a pneumatic servo system. The parameters of discrete-time model of plant are estimated by using the recursive least square method. Neural Network is utilized in order to compensate the nonlinear nature of plant such as compressibility of air and frictions present in cylinder. The experiment of a trajectory tracking control using the proposed control scheme has been performed and its effectiveness has been proved by comparing with the results of a model reference adaptive control.