• 한국정밀공학회지
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• 제21권5호
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• pp.55-63
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• 2004

This paper presents neural network based controller using the feedback error loaming technique for a heavy load pointing system. Also the mathematical model was developed to analyze heavy load pointing system. The control scheme consists of a feedforward neural network controller and a fixed-gain feedback controller. This neural network controller is trained so as to make the output of the feedback controller zero. The proposed controller is compared with the conventional PI controller through simulations, and the results show that the pointing accuracy of the proposed control system are improved against the disturbance induced by vehicle running on the bump course.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.57-61
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• 2001

A conceptional framework is proposed in which a general feedback predictive controller is taken to be a feedback interconnection of controller and GPC (General predictive Control). Numerical example are included to illustrate the procedure and to show the performance of the control system.

• 대한전기학회논문지
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• 제39권9호
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• pp.997-1005
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• 1990

Integral Error and State Feedback (IESF) controller which incorporates state feedback as a modern control scheme and integral action as a classical control scheme has better performance than that of conventional PID controller in linear time invariant system. But the structure of the IESF controller requires all the state variables of the system and is applicable only to pole assignable linear time invariant systems without time delay. Many industrial processes have large time delay and it is impossible to directly apply IESF control scheme to those processes. In this paper, a new controller structure, Modified Integral Error and State Feedback (MIESF) has been suggested in order to effectively control processes having time delay and its performance has been analyzed and its effectiveness has also been confirmed. As the proposed controller uses output feedback scheme based on integral error and state feedback (IESF) method, it can be simply designed by pole assignment algorithm irrespective of the order of the process. The MIESF controller can follow setpoint changes without overshoot. It is robuster than conventional Smith-Predictor plus PI(D) controller in case of occurring time delay mismatch and extra parameter mismatches between the process and the model. It can enhance control performance by intentional time delay mismatch.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.640-645
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• 2005

Closed-loop model-free optimization of positive feedback time delay controllers for dominant time delay systems is presented. Iterative feedback tuning (IFT) is applied to the tuning of positive feedback time delay controller. Three experiments are carried out to perform the model-free gradient descent optimization. The initial controller parameters and duration in specifying the cost function are suggested. The effects of step size, filter function and time weighting function on the performance of the optimized controlled are given. Simulation and experimental studies are included to demonstrate the effectiveness of the tuning scheme.

• 전기학회논문지
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• 제56권2호
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• pp.389-395
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• 2007

In this paper, we consider the robust non-fragile $H_{\infty}$ output feedback controller design method for uncertain descriptor systems with feedback and observer gain variations. The existence condition of observer-based robust and non-fragile $H_{\infty}$ output feedback controller and the controller design method are Presented on the basis of linear matrix inequality approach. The proposed robust non-fragile $H_{\infty}$ output feedback controller guarantees asymptotic stability, non-fragility, $H_{\infty}$ norm bound within a prescribed level in spite of disturbance, parameter uncertainty, and feedback/observer gain variations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1064-1067
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• 1996

This paper describes the design and implementation of an intelligent controller for continuous casting process. The proposed controller adopted a fuzzy control with feedback linearization. The simulation result shows that proposed intelligent controller is superior to the conventional PID controller.

• 한국지능시스템학회논문지
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• 제23권6호
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• pp.494-499
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• 2013

본 논문은 불확실한 연속시 단일입력 단일출력 pure-feedback 비선형 계통에 대해서 참고문헌 [15]에서 제안된 상태변수 궤환 적응 신경망 제어 알고리듬을 바탕으로 출력만이 측정 가능한 계통에 적용할 수 있는 출력 궤환 제어기를 제시한다. 고려하는 계통에 대한 출력 궤환 적응 신경망 제어기는 이 분야에서 아직까지 어느 문헌에서도 다루지 않은 주제이다. 제안된 출력 궤환 제어기는 백스테핑을 회피하여 상대적으로 간결한 제어 규칙과 단 하나의 신경망만이 사용된다는 [15]의 장점을 그대로 계승하며 적용되는 비선형 계통의 범주를 더 넓힌다는 의미를 가진다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.514-518
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• 2005

In this paper an adaptive fuzzy PI controller with feedback linearizing meth od is implemented to controlling flux and torque separately in induction motor. In this paper first decoupling of torque and flux which are outputs to be controlled, is achieved by using feedback linearization methodology. Then for reducing the effect of noise and rejection of disturbance, main part of controller which is adaptive PI fuzzy controller, is designed. Coefficients of PI controller are determined by defined fuzzy rules due to error dynamic. Inputs of fuzzy system are defined sliding surfaces which consist of torque and flux errors. The main contribution of this paper is effect reduction of noise and disturbance on torque and flux which is based on fuzzy logic and nonlinear control. At last the effectiveness of the proposed control scheme in presence of noise and load disturbance is simulated and comprised to applying sliding method. The results verify better effectiveness of the proposed method for effect reduction of noise and disturbance.

• 한국정밀공학회지
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• 제24권4호
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• pp.68-75
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• 2007

In this study, the ultimate goal is to acquire stability when turning around efficiently by using the controller which is applied partial feedback linearization of One-wheel Unicycle Robot. When moving around, linear controller could result in unstable factor according to widening operation range. So in order to reduce instability, 1 have developed Non-linear Controller using Partial Feedback Linearization. Compared with linear controller, Non-linear Controller guarantees the superiority of Regulating Control and Tracking Control in direct and also revolution motion of Robot. I'm sure of the Non-linear controller performance through many experiments.

• 한국지능시스템학회논문지
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• 제10권3호
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• pp.260-269
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• 2000

The fuzzy and state-feedback control systems have been applied in various areas from non-linear to linear systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. though apply back-propagation algorithm to the system, the convergence time a much. Besides, the state-feedback system is most widely used in industry due to its simple control structure and easily able to design the controller. but it is weak in complex system of higher degree and non-linear. In this paper presents the design of a fuzzy switching mode, it these two controllers work at different operation conditions, the advantages of both controller can be retained and the disadvantages can be removed. Between the Fuzzy and the State-feedback controlles, the good outputs are selected by the switching mode. Moreover it is powerful in complex system of higher degree and non-linear. In these sense compared with the state-feedback controller, the performance of the proposed controller was improvedin the section of linearization.