• Journal of Power Electronics
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• 제9권4호
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• pp.582-592
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• 2009

This paper proposes a new speed sensorless direct torque and flux controlled interior permanent magnet synchronous motor (IPMSM) drive. Closed-loop control of both the torque and stator flux linkage are achieved by using two proportional-integral (PI) controllers. The reference voltage vectors are generated by a SVM unit. The drive uses an adaptive sliding mode observer for joint stator flux and rotor speed estimation. Global asymptotic stability of the observer is achieved via Lyapunov analysis. At low speeds, the observer is combined with the high frequency signal injection technique for stable operation down to standstill. Hence, the sensorless drive is capable of exhibiting high dynamic and steady-state performances over a wide speed range. The operating range of the direct torque and flux controlled (DTFC) drive is extended into the high speed region by incorporating field weakening. Experimental results confirm the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1987-1992
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• 2004

A Variable Structure Model Reference Adaptive Controller (VS-MRAC) using state Variables is proposed for single input multi output systems. . The structure of the switching functions is designed based on stability requirements, and global exponential stability is proved. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time. The effect of input disturbances on stability and transients is investigated and shows preference to the conventional MRAC schemes with integral adaptation law. Sliding surfaces are independent of system parameters and therefore VS-MRAC is insensitive to system parameter variations. Simulation is presented to clear the theoretical results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.139-142
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• 1997

In this paper, a robust controller is proposed to achieve an accurate tracking for an uncertain nonlinear plant with actuator dynamics. The extent of parameter uncertainty can be quantified by using linear parameterization technique. A switching controller is proposed to guarantee the global asymptotic stability of the plant. In order to eliminate the chattering caused by the switching controller, a smoothing controller is designed using the boundary layer technique around the sliding surface and guarantees the uniform ultimate boundedness of the tracking error.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.947-948
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• 2006

This paper proposes a robust posture stabilization control method for wheeled mobile robots. To solve the robust posture stabilization, we introduce reference generation mode, reference tracking mode, and reference regulation mode. In reference generation mode, a kinematic time-invariant controller is used to generate the reference trajectory which starts from the initial posture of the actual robot to the desired posture. In reference tracking mode, a sliding mode position controller is employed in such a way that the actual robot can follow the reference trajectory in the desired forward or backward moving direction, even in the presence of the disturbances in the dynamics. In reference regulation mode, a sliding mode heading direction controller is used such that the actual robot can maintain the desired posture against the disturbances. In this way, robust posture stabilization can be achieved at almost all global regions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.173-176
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• 1999

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a Polishing robot. Using this method, the number of inference rules and the shape of membership functions are determined by the genetic algorithm. The fuzzy outputs of the consequent part are derived by the gradient descent method. Also, it is guaranteed that .the selected solution become the global optimal solution by optimizing the Akaike's information criterion expressing the quality of the inference rules. It is shown by simulations that the method of fuzzy inference by the genetic algorithm provides better learning capability than the trial and error method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.435-436
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• 2008

본 논문에서는 궤적이 슬라이딩 평면 밖에 있는 경우에 대해서도 LQ 성능을 보장하는 최적 슬라이딩 모드 제어기 설계 방법을 제안한다. 본 논문에서 제안한 방법에서는 슬라이딩 평면상에 있을 경우뿐만 아니라 슬라이딩 평면 밖에서도 LQ 성능을 보장하기 위해 최적 슬라이딩 평면을 이용하며 제어기에 슬라이딩 변수에 선형적으로 의존하는 항을 추가한다. 또한 제어기의 강인성을 위해 본 논문에서 제안된 새로운 외란 추정기법을 제어기와 결합한다. 마지막으로 컴퓨터 모의 실험을 통해 본 논문에서 제안한 제어기 설계 방법의 효율성을 검증하고자 한다.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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• pp.584-592
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• 2008

In this paper, we propose a new model of the magnetic control force exerted on the levitation object in magnetic levitation systems. The model assumes that the magnetic force is a function of the voltage applied to an electromagnet and the position of a levitation object. The function is not explicitly expressed but represented through a 2D lookup table constructed from the experimentally measured data. Unlike the conventional model that reveals only local characteristics of the magnetic force, the proposed model shows global characteristics satisfactorily. Specially devised measurement equipment is utilized in order to gather the data required for model construction. An experimental procedure to construct the model is presented. We apply the proposed model to designing a sliding mode controller for a lab-built magnetic system. The validity of the proposed model is illustrated by comparing the performances of the controller adopting the conventional model with that of the controller adopting the proposed model.

• International Journal of Automotive Technology
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• 제7권6호
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• pp.729-739
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• 2006

This paper describes an active fault-tolerant control system for an induction motor drive that propels an Electrical Vehicle(EV) or a Hybrid one(HEV). The proposed system adaptively reorganizes itself in the event of sensor loss or sensor recovery to sustain the best control performance given the complement of remaining sensors. Moreover, the developed system takes into account the controller transition smoothness in terms of speed and torque transients. In this paper which is the sequel of (Diallo et al., 2004), we propose to introduce more advanced and intelligent control techniques to improve the global performance of the fault-tolerant drive for automotive applications(e.g. EVs or HEVs). In fact, two control techniques are chosen to illustrate the consistency of the proposed approach: sliding mode for encoder-based control; and fuzzy logics for sensorless control. Moreover, the system control reorganization is now managed by a fuzzy decision system to improve the transitions smoothness. Simulations tests, in terms of speed and torque responses, have been carried out on a 4-kW induction motor drive to evaluate the consistency and the performance of the proposed fault-tolerant control approach.