• Title/Summary/Keyword: Tracking Error

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Measurement and Compensation of Heliostat Sun Tracking Error Using BCS (Beam Characterization System) (광특성분석시스템(BCS)을 이용한 헬리오스타트 태양추적오차의 측정 및 보정)

  • Hong, Yoo-Pyo;Park, Young-Chil
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.5
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    • pp.502-508
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    • 2012
  • Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

Frequency Tracking Error Analysis of LQG Based Vector Tracking Loop for Robust Signal Tracking

  • Park, Minhuck;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
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    • v.9 no.3
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    • pp.207-214
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    • 2020
  • In this paper, we implement linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) instead of conventional extended Kalman filter based vector tracking loop (EKF-VTL). The LQG-VTL can improve the performance compared to the EKF-VTL by generating optimal control input at a specific performance index. Performance analysis is conducted through two factors, frequency thermal noise and frequency dynamic stress error, which determine total frequency tracking error. We derive the thermal noise and the dynamic stress error formula in the LQG-VTL. From frequency tracking error analysis, we can determine control gain matrix in the LQG controller and show that the frequency tracking error of the LQG-VTL is lower than that of the EKF-VTL in all C/N0 ranges. The simulation results show that the LQG-VTL improves performance by 30% in Doppler tracking, so the LQG-VTL can extend pre-integration time longer and track weaker signals than the EKF-VTL. Therefore, the LQG-VTL algorithm is more robust than the EKF-VTL in weak signal environments.

Analysis of Heliostat Sun Tracking Error due to the Mirror Installation and Drive Mechanism Induced Errors (Heliostat 반사거울 설치 및 구동기구 유발 오차에 의한 태양추적오차의 해석)

  • Park, Young-Chil
    • Journal of the Korean Solar Energy Society
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    • v.29 no.3
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    • pp.1-11
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    • 2009
  • Heliostat sun tracking accuracy could be the most important requirement in solar thermal power plant, since it determines the overall efficiency of power plant. This study presents the effect of geometrical errors on the heliostat sun tracking performance. The geometrical errors considered here are the mirror canting error, encoder reference error, heliostat position error. pivot offset and tilt error, gear backlash and mass unbalanced effect error. We first investigate the effect of each individual geometrical error on the sun tracking accuracy. Then, the sun tracking error caused by the combination of individual geometrical error is computed and analyzed. The results obtained using the solar ray tracing technique shows that the sun tracking error due to the geometrical error is varying almost randomly. It also shows that the mirror canting error is the most significant error source, while the encoder reference error and gear backlash are second and the third dominant source of errors.

The Optimal Tracking Error of Active Stock Fund by Smart Beta Strategy (스마트 베타 전략에 따른 액티브 주식형 펀드의 최적 추적오차)

  • Jae-Hyun Lee
    • Asia-Pacific Journal of Business
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    • v.13 no.4
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    • pp.163-175
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    • 2022
  • Purpose - This study introduces a methodology for finding the optimal tracking error of active stock funds. Tracking error is commonly used in risk budgeting techniques as a concept of cost for alpha creation. Design/methodology/approach - This study uses a post-optimal smart beta portfolio that maximizes alpha under the given tracking error constraint. Findings - As a result of the analysis, the smart beta strategy that maximized alpha under the constraint of 0.15% daily tracking error shows the highest IR. This means the maximum theoretically achievable efficiency. In this regard, a fixed-effect panel regression analysis is conducted to evaluate the active efficiency of domestic stock funds. In addition to control variables based on previous studies, the effect of tracking error on alpha is analyzed. The alpha used in this model is calculated using the smart beta portfolio according to the size of the constraint of the tracking error as a benchmark. Contrary to theoretical estimates, in Korea, the alpha performance is maximized under a daily tracking error of 0.1%. This indicates that the active efficiency of domestic equity funds is lower than the theoretical maximum. Research implications or Originality - Based on this study, it is expected that it can be used for active risk management of pension funds and performance evaluation of active strategies.

Analysis of Sun Tracking Error Caused by the Heliostat Driving Axis Geometrical Error Utilizing the Solar Ray Tracing Technique (태양광선 제적추적기법을 이용한 Heliostat 구동축 기구오차에서 기인하는 태양추적오차의 분석)

  • Park, Young-Chil
    • Journal of the Korean Solar Energy Society
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    • v.29 no.2
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    • pp.39-46
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    • 2009
  • Heliostat, as a mirror system tracking the sun's movement, is the most important subsystem determining the efficiency of solar thermal power plant. Thus the accurate sun tracking performance under the various hazardous operating condition, is required. This study presents a methodology of development of the solar ray tracing technique and the application of it in the analysis of sun tracking error due to the heliostat geometrical errors. The geometrical errors considered here are the azimuth axis tilting error and the elevation axis tilting error. We first analyze the geometry of solar ray reflected from the heliostat. Then the point on the receiver, where the solar ray reflected from the heliostat is landed, is computed and compared with the original intended point, which represents the sun tracking error. The result obtained shows that the effect of geometrical error on the sun tracking performance is varying with time(season) and the heliostat location. It also shows that the heliostat located near the solar tower has larger sun tracking error than that of the heliostat located farther.

Compensation of Sun Tracking Error caused by the Heliostat Geometrical Error through the Canting of Heliostat Mirror Facets (반사거울 설치 방향 조정에 의한 Heliostat 기구오차에서 기인하는 태양추적오차의 보정)

  • Park, Young-Chil
    • Journal of the Korean Solar Energy Society
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    • v.29 no.6
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    • pp.22-31
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    • 2009
  • Canting is the optical alignment of mirror facets of heliostat such that the heliostat could focus the energy as a unit concentrator. Canting could improve the optical performance of heliostat and thus improves the efficiency of heliostat and ultimately improves the efficiency of the solar thermal power plant. This study discusses the effect of mirror canting, especially off-axis canting, used to compensate the sun tracking error caused by the heliostat geometrical errors. We first show that the canting could compensate the sun tracking error caused by the heliostat geometrical errors. Then we show that the proper canting time could exist, depending on the heliostat location. Finally we show how much the sun tracking performance could be improved by canting, by providing RMS sun tracking error. The limitation and caution of using canting to improve the sun tracking performance are also discussed.

Multipath Error Mitigation using Differenced Autocorrelation Function (자기 상관 차분 함수를 이용한 다중 경로 오차 감쇄 기법)

  • 최일흥;이상정
    • Journal of the Korea Institute of Military Science and Technology
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    • v.6 no.1
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    • pp.59-67
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    • 2003
  • Multipath is an inevitable error source in radio navigation system such as GPS, it causes signal tracking errors such as carrier tracking errors, code tracking errors. Since code tracking error is a dominant error in absolute positioning, this paper focuses on the improvement of code tracking performance. This paper proposes a method that detects the change of autocorrelation function's slope and mitigates the multipath error. Also, this paper shows the performance evaluation results by post-processing the digitized RF samples.

Robot Path Planning Method for Tracking Error Reduction (로봇의 추적오차 감소를 위한 궤적계획방법)

  • Kim, Dong-Jun;Kim, Gap-Il;Park, Yong-Sik
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.3
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    • pp.143-148
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    • 2001
  • A lot of robot trajectory tracking methods are proposed to enhance the tracking error, but irregular tracking errors are always accompanied and very hard to reduce it. Up to now, these irregular tracking errors are reduced by introducing more complicated control algorithms. But, it is intuitively obvious to reduce only the big errors selectively in the irregular ones for the better performance instead of using more complicated control algorithms. By the characteristics of the robot, big tracking errors of the end-effector are generated mostly due to the fast moving of joint. So, in this paper, we introduce a new method which reduce the big tracking errors by clippings the joint velocity with the constraint of given path. Using this method, desired trajectory tracking is obtained within the far reduced error bound. Also, this method is successfully applied to generate the path-constrained error reducing trajectories for 2-axis SCARA type robot.

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Performance Improvement of INS Velocity-aided GPS Carrier Tracking Loop (INS 속도 정보를 사용한 GPS 반송파 추적 루프의 성능 향상)

  • Kim Jeong-Won;Lee Sang-Jeong;Hwang Dong-Hwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.8
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    • pp.739-745
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    • 2006
  • This paper presents performance improvement of the INS velocity-adided GPS carier tracking loop. To this end, INS velocity-aided GPS carrier tracking loop was modeled as a feedfoward and a feedback loop system. In the phase tracking loop, it was shown that the tracking error caused by the dynamic motion of the vehicle can be compensated with the aiding of the INS information irrespective of the loop order and bandwidth. However, the signal trcking error increases as the INS error increases. It was also shown that in order to remove the tracking error caused by INS bias error, more than or equal to 2nd order PLL should be used. Experiments were carried out and the experimental results were compared with the analysis results.

A study on the information effect of tracking error affecting the sector ETF pricing (산업별 ETF의 가격결정에 영향을 미치는 추적오차의 정보효과에 관한 연구)

  • Byun, Young Tae;Lee, Sang Goo
    • Journal of Korea Society of Industrial Information Systems
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    • v.18 no.1
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    • pp.81-89
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    • 2013
  • The purpose of this study is to analyze the information effect about the pricing using the ETF price, the benchmark index, and the total tracking error between the ETF price and the benchmark index on the index ETF market and sector ETF markets. Furthermore, the total tracking error is distinguished between the market tracking error and the NAV tracking error. Summary of this study are as follows: First, While KODEX200 don't have impact factors on the price, the most sectors of ETF have the factors affecting the pricing decision. They are the day before the total tracking error or market tracking error. Second, for the ETF price of the most industry, we find that the day before the market tracking error have the price discovery function because it is a negative(-) coefficients. But NAV tracking error could not find such a feature. Finally, the sector ETF price of energy chemical, construction, IT, and semiconductor industries affected of the day before positive(+) impact by the benchmark index price.