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28 results on '"Song, Fazhi"'

6. Iterative Learning Identification with Bias Compensation for Stochastic Linear Time-Varying Systems

Author

Song, Fazhi, Liu, Yang, Yang, Zhile, Yang, Xiaofeng, He, Ping, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yue, Dong, editor, Peng, Chen, editor, Du, Dajun, editor, Zhang, Tengfei, editor, Zheng, Min, editor, and Han, Qinglong, editor

Published
2017
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9. Data filtering‐based parameter estimation algorithms for a class of nonlinear systems with colored noises.

Author

Zhang, Chen, Liu, Yang, Li, Li, and Song, Fazhi

Subjects
KALMAN filtering, PARAMETER estimation, NONLINEAR systems, ALGORITHMS, TRACKING algorithms, NOISE
Abstract

This article studies the data filtering‐based identification algorithms for a class of nonlinear system with autoregressive noise. By means of the data filtering technique and the hierarchical identification principle, the identification model is transformed into two sub‐identification models, and a filtering hierarchical gradient‐based iterative algorithm is proposed for improving parameter estimation accuracy and reducing computational burden. Meanwhile, to further improve the identification performance, the multi‐innovation identification theory is used to derived the filtering hierarchical multi‐innovation gradient‐based iterative algorithm. The gradient‐based iterative algorithm is given for comparison. The analysis shows that the filtering hierarchical gradient‐based iterative algorithm has smaller computational burden and can give more accurate parameter estimates than the gradient‐based iterative algorithm, and the filtering hierarchical multi‐innovation gradient‐based iterative algorithm can track time‐varying parameters based on the dynamical window data. Finally, the example part is provided to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Published
2023
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22. Communication design for multi-boards based on VME bus

Author

Zhenxian Fu, Song Fazhi, Wei Kai, and Yang Liu

Subjects
Engineering, Data acquisition, business.industry, Interface (computing), Embedded system, Bus, Local bus, business, Computer hardware, Control bus, Back-side bus, System bus, VMEbus
Abstract

As a widely used open-architecture computer bus ,VME bus is increasingly applied in military, aerospace, transportation and other large-scale control systems. Lithography, a very delicate and complicated integrated circuit manufacturing equipment, uses many circuit boards with VME interface in its control system, including one single-board computer, many movement control boards and one data acquisition board. This paper designs communication modules which include VME bus module and VME user-defined bus module for multi-boards in Lithography control system. VME bus module is designed for the communication between the single-board computer and movement control boards and VME user-defined bus is designed for the communication between movement control boards and data acquisition board. The experimental results demonstrate its effectiveness.

Published
2015

24. Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage.

Author

Li, Li, Tan, Jiubin, Song, Fazhi, Liu, Yang, and Cao, Jun

Subjects
ITERATIVE learning control, CRYSTAL filters, MATHEMATICAL models
Abstract

Iterative learning control (ILC) is one of the most popular tracking control methods for systems that repeatedly execute the same task. A system model is usually used in the analysis and design of ILC. Model-based ILC results in general in fast convergence and good performance. However, the model uncertainties and nonrepetitive disturbances hamper its practical applications. One of the commonly used solutions is the introduction of a low-pass filter, namely, the Q-filter. However, it is indicated in this paper that the existing Q-filter configurations compromise the servo performance, although improving the robustness. Motivated by the combination of performance and robustness, a novel Q-filter configuration in ILC is presented in this paper. Some practical considerations, such as the configuration of ILC in a feedback control system, the time delay compensation, and the learning coefficient, are provided in the implementation of the proposed ILC algorithm. The effectiveness and superiority of the proposed ILC versus existing Q-filter ILC are demonstrated by both theoretical analysis and experimental verification on a wafer stage. [ABSTRACT FROM AUTHOR]

Published
2018
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