• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.169-172
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• 2005

Genetic algorithm based predictor for lossless image compression is propsed. We describe a genetic algorithm to learn predictive model for lossless image compression. The error image can be further compressed using entropy coding such as Huffman coding or arithmetic coding. We show that the proposed algorithm can be feasible to lossless image compression algorithm.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.419-428
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• 2005

The screening test is increasingly being used for predicting future disease in the person screened and has raised concerns about reliability of the result of its procedure. We propose an improved estimator of the confidence interval for the positive predictive value(PPV) in screening test by simply taking inverse sinh transformation comparing to Gastwirth(1987) estimator and show its efficiency through the simulation study.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.263-264
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• 2007

This paper presents a model predictive controller for tracking control of the wheeled mobile robots (WMRs) subject to nonholonomic constraint. The input-output feedback-linearization method and the mode transformation are used. The performance of the proposed control algorithm is verified via computer simulation. It is shown that the control strategy is feasible.

• International Journal of Aeronautical and Space Sciences
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• 제12권1호
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• pp.16-23
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• 2011

In this paper, nonlinear model predictive control (NMPC) is addressed to develop formation guidance for multiple unmanned aerial vehicles. An NMPC algorithm predicts the behavior of a system over a receding time horizon, and the NMPC generates the optimal control commands for the horizon. The first input command is, then, applied to the system and this procedure repeats at each time step. The input constraint and state constraint for formation flight and inter-collision avoidance are considered in the proposed NMPC framework. The performance of NMPC for formation guidance critically degrades when there exists a communication failure. In order to address this problem, the modified optimal guidance law using only line-of-sight, relative distance, and own motion information is presented. If this information can be measured or estimated, the proposed formation guidance is sustainable with the communication failure. The performance of this approach is validated by numerical simulations.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.413-419
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• 1998

A novel order-reduction technique for model predictive control(MPC) is proposed based on the singular value decomposition(SVD) of a pulse response circulant matrix(PRCM) of a concerned system. It is first investigated that the PRCM (in the limit) contains a complete information of the frequency response of a system and its SVD decomposes the information into the respective principal directions at each frequency. This enables us to isolate the significant modes of the system and to devise the proposed order-reduction technique. Though the primary purpose of the proposed technique is to diminish the required computation in MPC, the clear frequency decomposition of the SVD of the PRCM also enables us to improve the robustness through selective excitation of frequency modes. Performance of the proposed technique is illustrated through two numerical examples.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.379-382
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• 2008

잡음환경 하의 회화에서 잡음량을 줄이고 신호처리 시스템의 성능을 향상시키기 위해서는 잡음량에 따라서 적응적으로 처리되는 신호처리 시스템이 필요하다. 따라서 본 논문에서는 선형예측계수를 사용하여 잡음량을 인식하는 방법을 제안하며, 본 잡음량 인식은 다양한 배경잡음에 의하여 열화된 3종류의 음성이 신경회로망에 의하여 학습되어진다. 본 실험에서는 Aurora2 데이터베이스를 사용하여 여러 잡음에 대하여 평균적으로 약 97.6% 이상의 양호한 인식결과를 확인할 수 있었다.

• 한국통신학회논문지
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• 제34권6B호
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• pp.641-647
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• 2009

본 논문은 임베디드 시스템에서 불필요한 전력 소모를 감소하기 위해 개선된 예측 동적 전력 관리 구조와 태스크 스케줄링 알고리듬을 제안한다. 제안된 알고리듬은 불필요한 전력 소모를 최소화하기 위해 미리 스케줄링을 한다. 제안된 예측 동적 전력 관리는 수행 오버 헤드를 경감하기 위해서 스케줄링 라이브러리를 제공한다. 실험 결과 제안된 알고리듬은 동적 전력 관리를 적용한 LLF 알고리듬과 비교하여 평균 22.3% 전력 소모 감소를 보인다.

• 전력전자학회논문지
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• 제19권3호
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• pp.249-256
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• 2014

This paper proposes a torque control method of permanent magnet synchronous motor, which has small torque ripple. The proposed control method is using the finite control set-model predictive control(FCS-MPC) strategy. An optimal input voltage vector minimizing a cost function is chosen among 6 passible active input voltage vectors following the FCS-MPC strategy. Then, a modulation factor for the optimal input voltage vector is computed to minimize the torque ripple. Thus, the proposed control method yields fast torque response and small torque ripple. The efficacy of the proposed method was verified through simulation and experiment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.421-424
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• 2003

This paper proposes the generalized predictive control(GPC) method of chaotic systems using a self-recurrent wavelet neural network(SRWNN). The reposed SRWNN, a modified model of a wavelet neural network(WNN), has the attractive ability such as dynamic attractor, information storage for later use. Unlike a WNN, since the SRWNN has the mother wavelet layer which is composed of self-feedback neurons, mother wavelet nodes of the SRWNN can store the past information of the network. Thus the SRWNN can be used as a good tool for predicting the dynamic property of nonlinear dynamic systems. In our method, the gradient-descent(GD) method is used to train the SRWNN structure. Finally, the effectiveness and feasibility of the SRWNN based GPC is demonstrated with applications to a chaotic system.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.1138-1145
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• 2013

A novel predictive current control strategy for a sparse matrix converter is presented. The sparse matrix converter is functionally-equivalent to the direct matrix converter but has a reduced number of switches. The predictive current control uses a model of the system to predict the future value of the load current and generates the reference voltage vector that minimizes a given cost function so that space vector modulation is achieved. The results show that the proposed controller for sparse matrix converters controls the load current very effectively and performs very well through simulation and experimental results.