• 조명전기설비학회논문지
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• 제17권1호
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• pp.112-115
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• 2003

산업 자동화의 고정밀도에 따라 서보 제어시스템은 강인제어가 요구되고 있다. 그러나 서보 제어시스템이 외란의 영향을 받게 되면 제어시스템의 강인제어는 어렵게 된다. 이에 대한 보완적인 한 방법으로 본 논문에서는 주 제어기(PID)와 미분 관리제어기의 혼합형 제어기법을 제시하였다. 주 제어기는 궤환제어기로서 동작하고, 미분 관리제어기는 외란에 의한 불안정한 상태에서 보조적인 동작을 한다. 미분 관리제어기의 강인성은 전통기의 속도제어에 의해서 확인하였다.

• 제어로봇시스템학회논문지
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• 제9권4호
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• pp.284-295
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• 2003

The servo tracks of disk drives are constructed at the time of manufacture with the equipment of servo track writer. Because of the imperfection of servo track writer, disk vibrations and head fluctuations during servo track writing process, the constructed servo tracks might deviate from perfect circles and take eccentric shapes. The servo track writing error should be corrected because it might cause interference with adjacent tracks and irrecoverable operation error of disk drives. The servo track writing error is repeated every disk rotation and so is periodic time function. In this paper, we propose a new correction algorithm of servo track writing error based on iterative teaming approach. Our correction algorithm can learn iteratively the servo track writing error as accurately as is desired. Furthermore, our algorithm is robust to system model errors, is computationally simple, and has fast convergence rate. In order to demonstrate the generality and practical use of our work, we present the convergence analysis of our correction algorithm and some simulation results.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.440-445
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• 2000

Robust tracking controller of optical disk drive(ODD) is designed using quantitative feedback theory(QFT). Nominal plant model is identified from real system through modal test. Uncertainties and control performance of tracking servo are specified, and robust controller satisfying these specifications is designed in the QFT framework. To verify the performances of designed controller, experiment are performed in a digital signal processor(DSP) environment, and experimental results are compared with simulations.

• 한국전자통신학회논문지
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• 제7권4호
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• pp.839-848
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• 2012

본 논문에서는 외란토크를 효과적으로 억제할 수 있는 AC 서보모터의 견실제어 방법을 제안한다. 제안된 제어기는 플랜트 모델에 기초한 피드포워드제어기와 안정화 피드백제어기로 구성된다. 피드포워드제어기는 공칭(nominal) 플랜트의 출력이 기준 속도명령을 정확히 추적하도록 설계되며 피드백제어기는 전체 폐루프시스템을 안정화시키는 역할을 한다. 피드백제어기는 임의로 선택될 수 있는 자유함수를 포함하는데 이 자유함수는 외란토크의 영향을 억제하고 제어기가 모델오차에 견실하게(robust) 동작되도록 선택될 수 있다. 컴퓨터 시뮬레이션을 통하여 제안된 제어방식이 기존의 제어방식들에 비해 우수한 제어성능을 가짐을 입증한다.

• 한국공작기계학회논문집
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• 제18권1호
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Journal of information and communication convergence engineering
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• 제7권2호
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• pp.125-130
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• 2009

A robust friction compensation scheme is proposed in this paper. The recurrent fuzzy neural network and friction parameter observer are developed with sliding mode based controller in order to obtain precise position tracking performance. For a servo system with incomplete identified friction parameters, a proposed control scheme provides a satisfactory result via some experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.21-21
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• 2000

In this paper, we design the state feedback gain using linear matrix inequality(LMI) to the multiobjective synthesis, in the magnetic bearing system with integral type servo system. The design objectives can be a H$\_$$\infty$/ performance, asymptotic disturbance rejection, time-domain constraints, on the closed-lnp pole location. To the end, we investigated the validity of the designed controller through results of simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.259-259
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• 2000

In the recent, the size of hardware is smaller and the structure is simpler, without reducing the performance of the digital controller. Accordingly, the fixed-point arithmetic is very important in the digital controller. This paper presents simulation to apply the robust control algorithms to DVDR servo controller using the floating-point and fixed-point arithmetic from the matlab. Also, it analyses and compares the performance of control algorithms in the each of point calculation and presents a method for improvement of drop in the performance, quantization error and overflow/underflow from using the fixed-point arithmetic

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.205-208
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• 1987

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.306-312
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• 1996

The performance of the failure detection algorithm may be greatly influenced by the model uncertainty. It is very important to design a robust failure detection system to the model uncertainty. In this paper, a design procedure to generate failure detection algorithm is proposed. The design procedure suggested is based on the concept of the‘threshold selector［1］’. The H$\infty$ control algorithm is used to derive a threshold selector which is robust to the model uncertainty, The threshold selector derived can be used to develop a failure detection system together with the weighted cumulative sum algorithm［3］. Computer simulation study showed that the failure detection system designed for an ISA(Integrated Servo Actuator) system by using the proposed method is robust to the model uncertainty.