• 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.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1160-1166
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• 2015

This paper proposes a decentralized robust adaptive control scheme for robot manipulators with input torque saturation in the presence of uncertainties. The control system should consider the practical problems that the controller gain coefficients of each joint may be nonlinear time-varying and the input torques applied at each joint are saturated. The proposed robot controller overcomes the various uncertainties and the input saturation problem. The proposed controller is comparatively simple and has no robot model parameters. The proposed controller is adjusted by the adaptation laws and the stability of the control system is guaranteed by the Lyapunov function analysis. Simulation results show the validity and robustness of the proposed control scheme.

• 전기학회논문지
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• 제57권4호
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• pp.610-616
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• 2008

This paper presents a new robust sensorless control system for high performance induction motor drives fed by a matrix converter with variable structure. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a variable structure approach based on model reference adaptive scheme. A Reduced Order Extended Luenberger Observer(ROELO) is also employed to bring better responses at the low speed operation. Experimental results are shown to illustrate the performance of the proposed system.

• KIEE International Transaction on Systems and Control
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• 제2D권2호
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• pp.108-114
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• 2002

This paper describes the design of a robust adaptive controller for a nonlinear dynamical system with unknown nonlinearities. These unknown nonlinearities are approximated by multilayered neural networks (MNNs) whose parameters are adjusted on-line, according to some adaptive laws far controlling the output of the nonlinear system, to track a given trajectory. The main contribution of this paper is a method for considering input constraint with a rigorous stability proof. The Lyapunov synthesis approach is used to develop a state-feedback adaptive control algorithm based on the adaptive MNN model. An overall control system guarantees that the tracking error converges at about zero and that all signals involved are uniformly bounded even in the presence of input saturation. Theoretical results are illustrated through a simulation example.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.80-83
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• 1988

In this paper a robust control law is presented which stabilezes overall system via pole reassignment and loop-shaping. A robust adaptive controller is designed combining this robust control law and a robust estimator.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.186-194
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• 2003

This paper proposes a combined controller frame of the adaptive robust control(ARC) and the sliding mode control(SMC) for the trajectory tracking control of the excavator to preserve the advantages of the both methods while overcoming their drawbacks, namely, asymptotic stability of adaptive system fir parametric uncertainties and guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbance. The suggested control technique is applied for the tracking of a straight-line motion of end-effector of manipulators, and through computer simulations, its trajectory tracking performances and the robustness to payload variation and uncertainties are illustrated.

• 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.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.269-282
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• 2007

This paper presents a robust control method via the intelligent adaptive backstepping design technique for stable walking of nine-link biped robots with unknown model uncertainties and external disturbances. In our control structure, the self recurrent wavelet neural network(SRWNN) which has the information storage ability is used to observe the uncertainties of the biped robots. The adaptation laws for all weights of the SRWNN are induced from the Lyapunov stability theorem, which are used for on-line controlling biped robots. Also, we prove that all signals in the closed-loop adaptive system are uniformly ultimately bounded. Through computer simulations of a nine-link biped robot with model uncertainties and external disturbances, we illustrate the effectiveness of the proposed control system.

• 대한기계학회논문집
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• 제14권3호
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• pp.513-525
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• 1990

본 연구에서는 ARSC의 이론적인 전개에 대해서 주로 설명하고자 한다. 제2 장에서는 ARSC의 구조를 자세히 기술하며, 제3장에 ARSC를 컴퓨터에 이식하기 위한 알 고리즘을 요약하여 제시한다. 또한, ARSC알고리즘이 총체적으로(globally) 수렴하며 안정하다는 이론적 증명에 대하여 제4장에서 언급하며, 마지막으로 제5장에 실시간 시 뮬레이션을 통하여 ARSC의 간단한 적용실례를 들었다. 실제로 본 ARSC는 엔드밀링의 절삭력 적응제어에 적용되었는데, 그 연구결과는 별도로 발표할 예정이다.

• 대한전자공학회논문지
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• 제25권12호
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• pp.1618-1624
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• 1988

In this paper, a robust discrete model reference adaptive controller is proposed using a generalized model reference adaptive algorithm for single-input single-output discrete systems. A signal dependent time-varying dead-zone is employed in a generalized adaptive control structure. This adaptive controller is shown to assure the boundedness of the signals of the system even in the presence of bounded external disturbance.