• 한국지능시스템학회논문지
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• 제20권2호
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• pp.220-225
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• 2010

본 논문에서는 전력 품질 개선 및 전력 계통 신뢰도 향상을 위한 방안으로서 STATCOM 발전 시스템의 시스템 모델링 및 강인 안정성에 대한 연구를 수행하고자 한다. STATCOM은 복잡한 전력 계통을 안정화하고 공급전원을 일정하게 유지할 목적으로 제안된 기술이다. 기존의 전력 보상 장치에 비해 전력 제어 범위가 상당히 넓은 편이며, 시스템 구성요소가 비선형적 움직임을 보이고 있다. 또한, 외부 환경에 따른 파라미터 변동이 있기 때문에 시스템 제어를 위한 새로운 기법 마련이 필요하다. 이를 해결하기 위하여, 시스템을 퍼지 이론을 통해 접근하여 모델링을 수행하게 되며, 강인 안정도 해석을 통해 시스템의 불확실성 요소에 대한 대비를 하게 된다.

• Journal of Power Electronics
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• 제9권6호
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• pp.892-902
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• 2009

This paper deals with the dynamic voltage control problem at the inverter end of a HVDC link when connected to a weak AC system which has the potential for harmonic instability and commutation failures. The dynamic voltage control problem is tackled with a STATCOM (Static Compensator), which not only provides a rapid recovery from harmonic instability and commutation failures but also offers a lower cost filter design for HVDC systems. PSCAD/EMTDC simulations are presented to validate the proposed topology and to demonstrate its robust performance.

• 대한전기학회논문지
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• 제36권9호
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• pp.670-677
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• 1987

The robustness and stability properties for a model reference adaptive control system with plant uncertainty are considered in this paper, using input-output stability theory. An error model for a typical adaptive control structure is extended to unmodelled dynamics in the plant model and then, the strictly positive real condition for global stability is examined. In general, since this condition can be easily violated due to unmodelled dynamics, a modified compensator which can be guaranteed Hev e SPR is introduced in the plant model and the effectiveness for the given structure is also given.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.263-266
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• 1998

This paper propose a prefilter type inverse control algorithm using chaotic neural networks. Since the chaotic neural networks show robust characteristics in approximation and adaptive learning for nonlinear dynamic system, the chaotic neural networks are suitable for controlling robotic manipulators. The structure of the proposed prefilter type controller compensate velocity of the PD controller. To estimate the proposed controller, we implemented to the Cartesian space control of three-axis PUMA robot and compared the final result with recurrent neural network(RNN) controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.95.2-95
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• 2001

Disturbance observer(DOB) based controller design is one of the most popular methods in the field of motion control. In this paper, a generalized disturbance compensation framework, called as robust internal-loop compensator(RIC) is introduced and an advanced design method of DOB is proposed based on the RIC. Mixed sensitivity optimization problem, which is the main issue of DOB design, is solved through the parameterization of DOB in the RIC framework. Different from conventional methods, Q-filter is separated in the mixed sensitivity optimization problem and the systematic design law for the DOB is proposed. This guarantees the robustness and optimality of the DOB and also enables the design for unstable plants.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• 전자공학회논문지B
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• 제33B권7호
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• pp.21-31
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• 1996

An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.9-11
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• 1998

Most of sensorless algorithms are based on motor equations including electrical and mechanical parameters. However, parameter variation and uncertain error decrease the accuracy of speed estimation of PMSM. This paper investigates the sensorless speed control of PMSM considering parameter variation. The proposed algorithm use the speed compensator which is robust in parameter variation and error. The simulation and experimental results indicate good performances.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.422-425
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• 1997

We consider the robust control problem for nonminimum phase(NMP) systems with parametric uncertainty which appear often in aircraft and missile control. First, a new method that makes such an uncertain NMP system to be factored as a interval minimum phase(MP) transfer function and a time delay term in the Pade approximation form has been presented. The controller to be proposed consists of a compensator $C_{Q}$(s) with Smith predictor in the internal model control(IMC) structure, so that it can have good robustness and performance against the structured uncertainty and the time delay behaviour due to NMP plant the $C_{Q}$(s) is designed on the MP model by using QFT. The stability and performance of overall system has been evaluated by the generalized Kharitonov theorem.rem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.370-373
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• 1991

This paper considers the linear multivariable model following servo system synthesis method in which linear optimal regulator problem is used to design controllers that make the response of the plant should be kept close to a specified ideal response of the model. The characteristics of this system is that the constructed system is robust in the presence of the constant disturbances or the parameter perturbations of the plant. Especially, the steady state offset is excluded for the ramp response of the model by direct feedforward compensator from the reference input.