• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.385-394
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• 2004

This paper proposes the generalized structure of a model-based disturbance rejection controller called a Robust Internal-loop Compensator (RIC). The framework consists of the RIC in the internal-loop to eliminate disturbances and a feedback controller in the external-loop to achieve nominal control performance. As the main contribution of this paper, we redefine the design problem of the RIC as a regulation control problem, then show that this new definition with the RIC structure provides more design flexibility and less implementation constraints. This is verified through a comparative structural analysis with Disturbance Observer (DOB) and Adaptive Robust Control (ARC). Two design examples of the RIC are given, along with practical issues that should be considered in the design procedure. The proposed framework is demonstrated by simulations of a rotary-type motor and experiments with a linear-type motor system.

• Journal of Platform Technology
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• v.6 no.3
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• pp.23-30
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• 2018

A motion pattern generation is a process of calculating a certain stable motion trajectory for stably operating a certain motion. A motion control is to make a posture of a robot stable by eliminating occurring disturbances while a robot is in operation using a pre-generated motion pattern. In this paper, a general method of motion pattern generation for a biped walking robot using universal approximator, learning neural networks, is proposed. Existing techniques are numerical methods using recursive computation and approximating methods which generate an approximation of a motion pattern by simplifying a robot's upper body structure. In near future other approaches for the motion pattern generations will be applied and compared as to be done.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.185-188
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• 2005

본 논문에서 신경망을 이용한 자계기반 자율주행 시스템의 조향 제어기 설계를 제안한다. 자율주행시스템에서 가장 중요한 핵심요소는 자계토로상의 센서의 현재위치를 파악하고 주행하는 것이다. 먼저 자계도로상의 현재위치를 파악하기 위한 방법으로, 첫 번째 자기쌍극자 모델식이 센서에서 측정된 자계와 일치함을 보였다. 두 번째 Peak Mapping법을 이용하여 외란으로 작용하는 지자계 성분을 제거할 수 있음을 입증하였다. 세 번째로 신경망을 이용하여 높이성분($B_{z}$)가 변하더라도 정확한 거리가 계측됨을 확인하였다. 따라서 신경망을 이용하면 소량의 메모리를 사용할 수 있으므로 실제 시스템에서 경제적인 효과를 볼 수 있고, 정확한 거리를 계측하므로 경로를 이탈하지 않고 자율주행이 가능한 시스템을 설계하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.168-175
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• 2010

The issue of rejecting periodic disturbances arises in various applications dealing with rotating machinery. A new method using DIDF (Dual-Input Describing Function) is presented for the rejection of periodic disturbances with uncertain frequency. This can be added to an existing feedback control system without altering the closed-loop system stability. The objective is to design a nonlinear compensator to secure specified oscillation amplitude and frequency which are the same as disturbances. We suggest two procedures to determine coefficients for DIDF's synthesis. The structure of the proposed DIDF is so simple that we can easily synthesize. A number of computer simulations were carried out to demonstrate the salient feature of the proposed DIDF compared to the conventional ones(that is, adaptive algorithms).

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.184-187
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• 2007

본 논문은 DSP Controller를 적용한 연료전지시스템의 유량제어에 관한 논문이다. 그리고 이 연구에서 사용된 시스템은 1kW급 계통연계 연료전지 시스템이다. 이 연료전지 시스템이 안정적으로 전원을 공급할 수 있도록 시스템에서 요구하는 공기 유량을 정확히 공급하도록 제어하는 것이 본 연구의 목적이다. 이 목적을 이루기 위해 공기 공급 장치에 PID 제어기를 설계하여 적용하였다. PID 제어기의 Gain값은 지글러 니콜스 Tuning 방식으로 정하였다. 이 제어기를 적용하여 실험한 결과, 적용 전 상태와 비교하면 맥동이 30% 저감하였고, 정상상태 오차가 제거되어 온도 변화와 같은 외란과 상관없이 정확한 요구 공기 유량을 공급함을 확인할 수 있었다. 그리고 부하가 변동함에 따라 해당 요구 공기 유량이 바뀔 때 1초 내에 그 요구 공기 유량을 추종하여 스택이 안정적으로 운전될 수 있도록 하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.898-906
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• 1999

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.65-81
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• 1998

Objective technology development has been carried out aiming performance improvement of the stabilized gun-pointing system for Type-4 tank. The full nonlinear simulation programs with gun bending modes and nonlinearities were developed to estimate, analyze and design the driving and stabilization system, and validated through the comparisons between simulations and test results of the existing Type-1 tank. The prototype is designed, fabricated, tested and evaluated on the test range as well as in the laboratory and followed by development and operational tests. The performance test results on stationary and on-the-move conditions are turned out to be superior to those of the advanced tanks developed in foreign countries.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.87-88
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• 2006

In this paper, tuning rules of the PID controller for load disturbance rejection are proposed incorporating with real-coded genetic algorithms(RCGAs). The optimal parameters sets of the PID controller are obtained based on a first-order plus time delay model and a RCGA. As for assessing the performance of the controller, criteria(ISE, IAE and ITAE) are adopted. Then tuning formulae are derived using the tuned parameters sets, potential tuning rule models and another RCGA. A simulation work is carried out to verify the effectiveness of the proposed rules.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.800-807
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• 1999

A Periodic disturbance canceller is proposed to compensate for the periodic disturbance due to cutting process in a CNC machining center. The periodic disturbance canceller estimates the Periodic disturbance without phase delay. This is achieved by using linear phase low-pass filter and frequency response reciprocal filter of plant at the frequency of the periodic disturbance. This method is implemented in the position control system of the CNC machining center with general disturbance compensators in order to compensate for both the frictional force and the periodic disturbance. The experimental results are described to show its effectiveness.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.89-94
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• 2001

The position control accuracy of a robot manipulator is significantly deteriorated when a long arm robot is operated at a high speed. This paper presents a very simple sliding mode control which eliminates multiple mode residual vibration in a robot manipulator. The neural network is used to avoid that sliding mode condition is deviated due to the change of system parameter and disturbance. This paper is suggested control system which designed by sliding mode controller using neural network. The effectiveness of proposed scheme is demonstrated through computer simulation.