• 한국산학기술학회논문지
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• 제11권5호
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• pp.1597-1600
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• 2010

본 논문은 비선형 동적 신경망을 이용하여 직접 제어에 관한 연구이다. RBF 신경망을 이용한 제어입력과 근사화 오차 및 외란의 영향을 제거하기 위한 보조제어 입력으로 구성하였다. 외란이나 근사화 오차에 관계없이 플랜트와 기준모델 사이의 오차가 0이 되도록 하는 알고리즘을 구할 수 있었다. 시뮬레이션 결과는 매우 효과적이며 비선형 시스템의 만족스러운 학습 성능을 증명하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.54-60
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• 2021

Monte-Carlo GO is a computer GO program that is sufficiently competent without using knowledge expressions of IGO. Although it is computationally intensive, the computational complexity can be reduced by properly pruning the IGO game tree. Here, I achieve this by using a potential model based on the knowledge expressions of IGO. The potential model treats GO stones as potentials. A specific potential distribution on the GO board results from a unique arrangement of stones on the board. Pruning using the potential model categorizes legal moves into effective and ineffective moves in accordance with the potential threshold. Here, certain pruning strategies based on potentials and potential gradients are experimentally evaluated. For different-sized boards, including an official-sized board, the effects of pruning strategies are evaluated in terms of their robustness. I successfully demonstrate pruning using a potential model to reduce the computational complexity of GO as well as the robustness of this effect across different-sized boards.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.64-69
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• 2021

In this paper, we have proposed a new internal model control structure (IMC). It is aimed at unstable overactuated multivariable systems whose transfer matrices are singular and unstable. The model inversion problem is essential to understand this structure. Indeed, the precision between the output of the process and the setpoint is linked to the quality of the inversion. This property is preserved in the presence of an additive disturbance at the output. This inversion approach proposed in this article can be applied to multivariable systems with no minimum phase or minimum phase shift with or without delays in their transfer matrices. It is proven by an example of simulation through which we have shown its good performance as a guarantee of stability, precision as well as rapidity of system responses despite the presence of external disturbances and we have tested this control structure in the frequency domain hence the robustness of the IMC.

• 정보보호학회논문지
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• 제29권5호
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• pp.1099-1116
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• 2019

다양한 산업 분야 및 주요 기반시설에서 사용되는 산업 제어시스템의 보안 위협에 대응하기 위해 산업용 제어기기에 대한 보안 평가 제도가 도입되어 운영되고 있다. 산업용 제어기기의 보안 평가 시험은 산업 제어시스템을 구성하는 각 구성요소별 보안요구사항을 시험하는 것으로서 기기 자체의 보안 기능에 대한 시험과 통신 견고성에 대한 시험을 포함한다. 본 논문에서는 국내 외 산업용 제어기기의 인증 시험인 EDSA, Achilles, 산업 제어시스템 보안요구사항(TTA 표준) 및 각각의 통신 견고성 시험의 특징을 분석하였다. 통신 견고성 시험은 퍼징 및 과부하 패킷을 전송하는 동안 기기의 정상동작 여부를 확인하는 것으로 기존의 시험환경 및 기준은 대부분 임베디드 장치의 특징에 초점이 맞춰져 있어 다양한 산업용 제어기기에 적용하기에는 한계점이 존재한다. 이에 본 논문에서는 산업 제어시스템에서 사용되는 제어 H/W, 제어 S/W, 현장장치, 네트워크 장비의 특성을 반영한 통신 견고성 시험환경 구축방안 및 시험시 고려해야할 사항을 제시하였다. 향후에는 제안한 기기별 통신 견고성 시험 기준을 실제 제품에 적용할 때 발생하는 이슈사항을 확인하고 이에 대한 해결책을 제시하고자 한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권9호
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• pp.663-669
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• 2004

The mobile tole-cardiology system is the new research area that support an ubiquitous health care based on mobile telecommunication networks. Although there are many researches presenting the modeling concepts of a GSM-based mobile telemedical system, practical application needs to be considered both compression performance and error corruption in the mobile environment. This paper evaluates three wavelet ECG compression algorithms over CDMA networks. The three selected methods are Rajoub using EPE thresholding, Embedded Zerotree Wavelet(EZW) and Wavelet transform Higher Order Statistics Coding(WHOSC) with linear prediction. All methodologies protected more significant information using Forward Error Correction coding and measured not only compression performance in noise-free but also error robustness and delay profile in CDMA environment. In addition, from the field test we analyzed the PRD for movement speed and the features of CDMA 1X. The test results show that Rajoub has low robustness over high error attack and EZW contributes to more efficient exploitation in variable bandwidth and high error. WHOSC has high robustness in overall BER but loses performance about particular abnormal ECG.

• 한국산업융합학회 논문집
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• 제24권1호
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• pp.1-7
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• 2021

In this paper, we presented the experimental basis for the theoretical background and robustness of the Convolutional Neural Network for object recognition based on artificial intelligence. An experimental result was performed to visualize the weighting filters and feature maps for each layer to determine what characteristics CNN is automatically generating. experimental results were presented on the trend of learning error and identification error rate by checking the relevance of the weight filter and feature map for learning error and identification error. The weighting filter and characteristic map are presented as experimental results. The automatically generated characteristic quantities presented the results of error rates for moving and rotating robustness to geometric changes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.634-637
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• 1994

This paper presents a CMAC network based controller on the basis of Lyapunov theory. CMAC network is employed to approximate and to compensate the uncertainties induced by inaccurate modelling of the system. For the improvement of robustness under the bounded disturbances and the approximation error of the CMAC, the adaptation scheme with a deadzone and an additional control input are developed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.1113-1119
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• 1989

Neural network control has many innovative potentials for intelligent adaptive control. Among many, it promises real time adaption, robustness, fault tolerance, and self-learning which can be achieved with little or no system models. In this paper, a dynamic robot controller has been developed based on a backpropagation neural network. It gradually learns the robot's dynamic properties through repetitive movements being initially trained with a PD controller. Its control performance has been tested on a simulated PUMA 560 demonstrating fast learning and convergence.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.294-300
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• 2009

The neural network with radial basis function is introduced for position tracking control of AC servo drive with the existence of system uncertainties. An adaptive robust term is applied to overcome the external disturbances. The proposed controller is implemented on a high performance digital signal processing DSP TMS320C6713-300. The stability and the convergence of the system are proved by Lyapunov theory. The validity and robustness of the controller are verified through simulation and experimental results