• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1138-1141
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• 2003

This paper proposes a new speed and flux estimation method which has the robustness against the variation of the electrical parameters of the motor and the superiority in the dynamic characteristics compared with the conventional sensorless schemes. In the proposed method, the stator currents and the rotor fluxes are observed on the stationary reference frame using the sliding mode concept. And the rotor speed is estimated using the current estimation errors and the observed rotor fluxes based on the Lyapunov stability theory. Also a design method of the observer gain is proposed to minimize the effect of the speed estimation error on the rotor flux observation. The experimental results verified that the proposed method shows more robust and improved performances than the previous estimation method under the variations of motor resistance and inductance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.386-388
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• 1996

This paper presents the learning controller for robot manipulators to track the desired trajectory exactly. The learning controller, based on the Lyapunov theory, consists of a fixed PD action and a repetitive action for the purpose of feedforward compensation which is adjusted utilizing a linear combination of the velocity and position errors. The learning controller Is often used In case of the desired trajectories are periodic tasks, and has advantage that it periodically converges to zero even if we don't know the exact dynamic parameters. In this paper, we show that the position and velocity errors of robot manipulators converge to zero sa time goes infinite for the input is periodic function and show a good trajectory tracking performance In the cartesian space.

• 전기학회논문지
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• 제66권1호
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• pp.153-158
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• 2017

This paper investigates a robust low-complexity design problem for tracking control of uncertain switched pure-feedback systems in the presence of unknown control direction. The completely unknown non-affine nonlinearities are assumed to be arbitrarily switched. By combining the nonlinear error transformation technique and Nussbaum-type functions, a robust tracking controller is designed without using any adaptive function approximators. Thus, compared with existing results, the proposed control scheme has the low-complexity property. From Lyapunov stability theory, it is shown that the tracking error remains within the preassigned transient and steady-state error bounds.

• 전기학회논문지
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• 제66권1호
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• pp.159-164
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• 2017

In this paper, we propose a method of designing the sampled-data tracking controller for nonlinear systems expressed by the Takagi-Sugeno (T-S) fuzzy model. A sufficient condition that asymptotically stabilizes the state error between the linear reference model and the T-S fuzzy model is derived in terms of linear matrix inequalities. To this end, error dynamics are constructed, and the exact discretization method and the Lyapunov stability theory are employed in this paper. Finally, we validate the proposed method through the simulation example.

• 전기학회논문지
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• 제61권7호
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• pp.1019-1023
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• 2012

This paper considers a model predictive control problem of discrete-time constrained systems with time-varying delay. For this problem, a delay dependent state feedback control approach is used to achieve asymptotic stabilization of systems with input constraints. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find cost monotonicity condition of the model predictive control algorithm which guarantee the closed loop stability. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1644-1645
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• 2007

This paper proposes an adaptive sliding mode control method for trajectory tracking of nonholonomic mobile robots with model uncertainties and external disturbances. The kinematic model represented by polar coordinates are considered to design a robust control system. Wavelet neural networks (WNNs) are employed to approximate arbitrary model uncertainties in dynamics of the mobile robot. From the Lyapunov stability theory, we derive tuning algorithms for all weights of WNNs and prove that all signals of an adaptive closed-loop system are uniformly ultimately bounded.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.1929-1931
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• 2001

An adaptive fuzzy logic controller to regulate molten steel level in the strip casting process is presented, where parameters of fuzzy controllers are adapted stably by using Lyapunov-stability theory and a switching controller is used together to deal with the approximation error of fuzzy logic system. The level error is proven to converge to zero asymptotically. In the simulation, the clogging/unclogging of a stopper nozzle is considered and overcome by the proposed controller. Robustness to uncertainty is shown to be superior to conventional PI controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2087-2088
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• 2001

In this paper we presents a speed controller for permanent magnet synchronous motor using adaptive backstepping technique. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed control and adaptive law is proved to be asymptotically stable by the Lyapunov stability theory.

• 한국항행학회논문지
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• 제17권6호
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• pp.679-686
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• 2013

본 논문에서는 데이터 통신을 이용하는 네트워크 제어 시스템에서 데이터 전송 지연에 의한 시스템 안정성 조건을 리아프노프 이론을 이용하여 새로이 유도하였다. 제안된 안정조건은 기존의 복잡한 계산에 의한 결과에 비하여 매우 간단한 형태이며 쉽게 계산될 수 있다. 또한, 기존에 연구된 결과들을 포함하여 적용될 수 있는 조건임을 보였다. 시뮬레이션을 통하여 기존의 결과에 비해 성능 면에서 우수하고 안정성 판단에 있어 덜 제한적임을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control.