• 한국지능시스템학회논문지
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• 제12권6호
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• pp.554-558
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

• 대한전자공학회논문지
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• 제18권3호
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• pp.35-41
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• 1981

최근에 활발히 연구되고 있는 model reference adaptive control 이론을 microprocessor를 사용하여 직류전동기의 속도제어에 적용할 수 있음을 보였다. 본 논문에서는 일차로 근사시킨 reference model을 설정하고 model의 output과 motor의 output의 처리가 영에 수렴하도록 하였다. 먼저 computer simulation에 의해 reference 입력과 부하의 변동에 따른 출력을 살펴본 후 microprocessor M 6800을 이용하여 직류전동기를 제어하였는데 input 및 부하의 급격한 변동에 잘 적용하는 특성을 보여 주었다.

• 전자공학회논문지B
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• 제30B권5호
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1471-1474
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제22권8호
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• pp.393-398
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• 2016

군집 적응형 시스템(Collective Adaptive System, CAS)은 다수의 에이전트를 포함하는 적응형 시스템으로, 에이전트들 간의 헙업을 통해 목표를 수행한다. 협업을 기반으로 시스템의 목표를 수행하는 CAS는 복수의 에이전트들 간의 상호작용에 대한 테스트가 필수적이다. 본 연구에서는 CAS를 테스트하기 위한 하나의 방법으로 태스크 기반의 테스트 모델을 적용하여 모델 기반 테스팅을 하는 것에 대한 타당성을 분석한다. 분석을 위해 CAS의 한 사례로 스마트 홈 시스템을 적용하였고, 그 결과 태스크 모델을 수정 및 확장하면 CAS의 목표 달성 여부를 판별할 수 있는 체계적인 테스트 케이스 생성이 가능한 것을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.331-334
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• 1996

It is a well-known problem that the adaptive control has a poor transient response. In order to improve this problem, the scheme that model-reference adaptive control (MRAC) uses the genetic algorithm (GA) in the search for parameters is proposed. Use genetic algorithm (GA) in the searching for controller's parameters set and conventional gradient method for fine tuning. And show the reduction of the oscillations in transient response comparing with the conventional MRAC.

• 대한전기학회논문지
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• 제33권1호
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• pp.17-20
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• 1984

The motivation in this paper is in constructing the controller with faster adapting speed than the one using the errors between the states of the plant and the model as the adaptive criterion. In the first part of this work, the adaptive law is found by using the state errors. In the later part, the adaptive law is obtained by introducing the companion model method. Finally the justification for the adaptive speed characteristics are compared.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.136-138
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• 1997

This paper proposes a design method to improve the performance of Indirect Adaptive Controllers using a CP net. This hybrid control architecture consists of Indirect Adaptive Controllers and CP net Controller. The performance of a single Adaptive Controller, multi Adaptive Controllers and the proposed model is compared by control problems. The simulation results show that the proposed model is superior to the others in most cases, in regard of not only learning speed but also control problems.