• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.366-369
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• 1991

A nonlinear controller based on feedback linearization method is proposed for an electromagnetic suspension system. After exactly linearizing the system with nonlinear feedback, linear control technique is applied. Modeling of stagger typed magnet is introduced and controlled for not only levitation, but guidance. By the feedback linearization, the nonlinear, MIMO system is linearized and decoupled, so we can use linear control law. The simulation of this system control skim is demonstrated. Robustness properties of the proposed controller with respect to the load variations and external disturbance is also analyzed for a multi input multi output system. In this properties, the boundary of variation is proposed.

• 전기전자학회논문지
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• 제17권1호
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• pp.83-88
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• 2013

본 논문에서는 입력과 출력에 동시에 시간 지연이 존재하는 피드포워드 비선형시스템에 대한 출력 피드백 제어 방법을 제안한다. 제안한 출력 피드백 제어기는 선형관측기와 선형제어기로 구성된다. Lyapunov-Krasovskii 정리를 이용하여 임의의 크기를 갖는 시간지연에 대하여 전역적 점근 안정도를 보장함을 증명한다. 마지막으로 제안한 결과의 유효성을 증명하기 위하여 모의실험 예제를 제공한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.271-274
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• 1995

This paper is concerned with the problem of robust stabilization of uncertain single-input and single-output nonlinear systems. Based on the input/output linearization approach for nonlinear state feedback synthesis in conjunction with Lyapunov methods, a stabilizing state feedback controller is proposed. Compared with the controllers reported in the control literature, instead of uniform ultimate boudedness, the controller proposed in this paper can guarantee uniform asymptotic stability of nonlinear systems in the presence of uncertainties. The required information about uncertain dynamics in the system is only that the uncertainties are bounded in Euclidean norm by known functions of the system state.

• 대한전기학회논문지
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• 제41권3호
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• pp.292-299
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• 1992

A nonlinear feedback linearizing control method for an EMS (Electro-Magnetic Suspension) system is proposed. After linearzing the system using the exact linearizing method, conventional linear system control theory has been applied. Robustness properties of the proposed controller with respect to the load variations is also analysed for a single magnet suspension system. Computer simulation is carried out in order to compare the performance of the proposed controller with that of the existing controller designed by using Taylor series expansion around nominal points.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1227-1233
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• 1993

In this paper we present the differential geometric approach for the analysis and design of sliding modes in nonlinear variable structure feedback systems. We also design the robust controller for the nonlinear system using variable structure control theory on the basis of differential geometric methods and feedback linearization applying Min-Max control based on the Lyapunov second method. The robustness against parameter uncertainties for robot manipulators with flexible joint is considered. Simulation results are presented and show the advantage of the proposed nonlinear control method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.176-179
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• 2000

This paper addresses a fuzzy controller for nonlinear systems control using a pole placement in a specified disk and fuzzy controller is redesign for Intelligent digital redesign method. for nonlinear system, we obtain continuous time state feedback gain that guarantee stability of globally TS fuzzy system. The feedback gain is satified pole placement in a specified disk region so that the closed loop system is stable, For digital control redesgin of continuous time TS fuzzy model, we does state matching and obtain feedback gain of digital controller. Finally, it is shown that the proposed method is feasible through a computer simulation.

• 전기학회논문지
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• 제58권9호
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• 전력전자학회논문지
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• 제4권1호
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• pp.43-49
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• 1999

본 연구에서는 비선형 시스템을 선형 시스템으로 변환시키는 미분기하이론에 기초를 둔 비선형 궤환 선형화 기법을 유도전동기와 같은 비선형 시스템의 제어에 응용함으로써 완전한 비간섭 시스템을 얻을수 있음을 보였다. 또한, 엘리베이터와 같은 부하의 정속도 운전시 효율제어를 위해 회전자 자속을 변화시킬 때 이의 영향을 받아 값이 바뀌는 인덕턴스와 온도에 따라 가장 변화가 심한 회전자저항을 위한 추정알고리즘을 제안하고 이의 성능을 평가해 보기 위하여 시뮬레이션과 실험을 수행하였다.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.559-564
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• 2002

This Paper Proposes a design method of a fuzzy output feedback controller for the nonlinear systems with the unknown time- delay. Recently, Cao et ai. proposed a stabilization method for the nonlinear time-delay systems using a fuzzy controller when the time-delay is known. However, the time-delay is likely to be unknown in practical. We represent the nonlinear systems with the unknown time-delay by Takagi-Sugeno (T-5) fuzzy model and design the fuzzy observer and the parallel distributed compensation (PDC) law based on this observer. By applying Lyapunov-Krasovskii theorem to the closed-loop system, the sufficient condition for the asymptotic stability of the equilibrium Point is derived and converted into the linear matrix inequality (LMI) Problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.187-190
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• 2003

In this paper, we address the robust adaptive backstepping controller using fuzzy neural network (FHIN) for a class of uncertain output feedback nonlinear systems with disturbance. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The state estimation is solved using K-fillers. All unknown nonlinear functions are approximated by FNN. The FNN weight adaptation rule is derived from Lyapunov stability analysis and guarantees that the adapted weight error and tracking error are bounded. The compensated controller is designed to compensate the FNN approximation error and external disturbance. Finally, simulation results show that the proposed controller can achieve favorable tracking performance and robustness with regard to unknown function and external disturbance.