- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 North American Power Symposium (NAPS) - Wichita, KS, USA (2019.10.13-2019.10.15)] 2019 North American Power Symposium (NAPS) - Study of Smart Grid Protection Challenges with High Photovoltaic Penetration
摘要： We present an automatic parameter setting method to achieve an accurate second-order Kalman ?lter tracker based on a steady-state performance index. First, we propose an ef?cient steady-state performance index that corresponds to the root-mean-square (rms) prediction error in tracking. We then derive an analytical relationship between the proposed performance index and the generalized error covariance matrix of the process noise, for which the automatic determination using the derived relationship is presented. The model calculated by the proposed method achieves better accuracy than the conventional empirical model of process noise. Numerical analysis and simulations demonstrate the effectiveness of the proposed method for targets with accelerating motion. The rms prediction error of the tracker designed by the proposed method is 63.8% of that with the conventional empirically selected model for a target accelerating at 10 m/s2.
关键词： steady-state performance,Tracking ?lter,process noise,Kalman ?lter,parameter setting
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Performance Degradation in aSi/cSi Heterojunction Solar Cells by Glassy Dynamics
摘要： We present an automatic parameter setting method to achieve an accurate second-order Kalman ?lter tracker based on a steady-state performance index. First, we propose an ef?cient steady-state performance index that corresponds to the root-mean-square (rms) prediction error in tracking. We then derive an analytical relationship between the proposed performance index and the generalized error covariance matrix of the process noise, for which the automatic determination using the derived relationship is presented. The model calculated by the proposed method achieves better accuracy than the conventional empirical model of process noise. Numerical analysis and simulations demonstrate the effectiveness of the proposed method for targets with accelerating motion. The rms prediction error of the tracker designed by the proposed method is 63.8% of that with the conventional empirically selected model for a target accelerating at 10 m/s2.
关键词： steady-state performance,Tracking ?lter,process noise.,Kalman ?lter,parameter setting
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 16th International Conference on Group IV Photonics (GFP) - Singapore, Singapore (2019.8.28-2019.8.30)] 2019 IEEE 16th International Conference on Group IV Photonics (GFP) - Ultra Low-Loss Silicon Waveguides for 200 mm Photonics Platform
摘要： We present an automatic parameter setting method to achieve an accurate second-order Kalman ?lter tracker based on a steady-state performance index. First, we propose an ef?cient steady-state performance index that corresponds to the root-mean-square (rms) prediction error in tracking. We then derive an analytical relationship between the proposed performance index and the generalized error covariance matrix of the process noise, for which the automatic determination using the derived relationship is presented. The model calculated by the proposed method achieves better accuracy than the conventional empirical model of process noise. Numerical analysis and simulations demonstrate the effectiveness of the proposed method for targets with accelerating motion. The rms prediction error of the tracker designed by the proposed method is 63.8% of that with the conventional empirically selected model for a target accelerating at 10 m/s2.
关键词： steady-state performance,Tracking ?lter,process noise.,Kalman ?lter,parameter setting
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Macao, Macao (2019.12.1-2019.12.4)] 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Optimal Operation of Concentrating Solar Power Station in Power System with High Penetration of Photovoltaic Generation
摘要： We present an automatic parameter setting method to achieve an accurate second-order Kalman ?lter tracker based on a steady-state performance index. First, we propose an ef?cient steady-state performance index that corresponds to the root-mean-square (rms) prediction error in tracking. We then derive an analytical relationship between the proposed performance index and the generalized error covariance matrix of the process noise, for which the automatic determination using the derived relationship is presented. The model calculated by the proposed method achieves better accuracy than the conventional empirical model of process noise. Numerical analysis and simulations demonstrate the effectiveness of the proposed method for targets with accelerating motion. The rms prediction error of the tracker designed by the proposed method is 63.8% of that with the conventional empirically selected model for a target accelerating at 10 m/s2.
关键词： Kalman ?lter,steady-state performance,Tracking ?lter,process noise,parameter setting
更新于2025-09-19 17:13:59