• Title/Summary/Keyword: robust H₂filter

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An algorithm for pahse detection using weighting function and the design of a phase tracking loop (가중치 함수를 이용한 위상 검출 알고리즘과 위상 추적 루프의 설계)

  • 이명환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.9A
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    • pp.2197-2210
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    • 1998
  • In the grand alliance (GA) HDTV receiver, a coherent detection is empolyed for coherent demodulation of vestigial side-band (VSB) signal by using frequency and phaselocked loop(FPLL) operating on the pilot carrier. Additional phase tracking loop (PTL) employed to track out phase noise that has not been removed by the FPLL in theGA system. In this paper, we propose an algorithm for phase detection which utilizes a weighting function. The simplest implementation of the proposed algorithm using te sign of the Q channel component can be tractable by imposing a phase detection gain to the loop gain. It is obserbed that the propsoed algorithm has a robust characteristic against the performance of the digital filters used for Q channel estimation. A second goal of this paper is to introduce a gain control algorithm for the PTL in order to provide an effective implementation of the proposed phase detection algorithm. And we design the PTL through the realization of the simplified digital filter for H/W reduction. The proposed algorithms and the designed PTL are evaluated by computer simulation. In spite of using the simplified H/W structure, simulation results show that the proposed algorithms outperform the coventional PTL algorithms in the phase detection and tracking performance.

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Design of $H_{\infty}$Controller for the inverted pendulum system (도립진자 시스템의 $H_{\infty}$ 제어기 설계)

  • Seo, Kang-Myun;Kang, Moon-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.10
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    • pp.1796-1803
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    • 2006
  • This Paper describes a systematic method for designing the $H_{\infty}$ controller for the inverted pendulum which is a nonlinear and single-input double-outputs system. In particular, the open-loop system is conbined with a pre-filter to shape the open-loop transfer function for the sensitivity function ind the complementary sensitivity function to be kept the desirable frequency characteristics. Consequently, the loop shaping technique of the open-loop transfer function reduces the impacts of the model uncertainties, measurement noises and exogenous disterbances on the dynamic characteristics of the inverted pendulum. The results of simulation and experiment show the efficiency of the proposed control method comparing with conventional PID control method.

Facial Image Analysis Algorithm for Emotion Recognition (감정 인식을 위한 얼굴 영상 분석 알고리즘)

  • Joo, Y.H.;Jeong, K.H.;Kim, M.H.;Park, J.B.;Lee, J.;Cho, Y.J.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.801-806
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    • 2004
  • Although the technology for emotion recognition is important one which demanded in various fields, it still remains as the unsolved problem. Especially, it needs to develop the algorithm based on human facial image. In this paper, we propose the facial image analysis algorithm for emotion recognition. The proposed algorithm is composed as the facial image extraction algorithm and the facial component extraction algorithm. In order to have robust performance under various illumination conditions, the fuzzy color filter is proposed in facial image extraction algorithm. In facial component extraction algorithm, the virtual face model is used to give information for high accuracy analysis. Finally, the simulations are given in order to check and evaluate the performance.

Adaptive On-line State-of-available-power Prediction of Lithium-ion Batteries

  • Fleischer, Christian;Waag, Wladislaw;Bai, Ziou;Sauer, Dirk Uwe
    • Journal of Power Electronics
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    • v.13 no.4
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    • pp.516-527
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    • 2013
  • This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.