Zhichun Mu, KeLiu, Zichao Wang, Datai Yu, D. Koshal, and D. Pearce, Application of Genetic Algorithms in Identification of Linear Time-Varying System, J. Univ. Sci. Technol. Beijing, 7(2000), No. 1, pp. 58-62.
Cite this article as:
Zhichun Mu, KeLiu, Zichao Wang, Datai Yu, D. Koshal, and D. Pearce, Application of Genetic Algorithms in Identification of Linear Time-Varying System, J. Univ. Sci. Technol. Beijing, 7(2000), No. 1, pp. 58-62.
Zhichun Mu, KeLiu, Zichao Wang, Datai Yu, D. Koshal, and D. Pearce, Application of Genetic Algorithms in Identification of Linear Time-Varying System, J. Univ. Sci. Technol. Beijing, 7(2000), No. 1, pp. 58-62.
Citation:
Zhichun Mu, KeLiu, Zichao Wang, Datai Yu, D. Koshal, and D. Pearce, Application of Genetic Algorithms in Identification of Linear Time-Varying System, J. Univ. Sci. Technol. Beijing, 7(2000), No. 1, pp. 58-62.
Information Engineering School, University of Science & Technology Beijing, Beijing 100083, China
School of Engineering, University of Brighton, Brighton, UK
中文摘要
By applying genetic algorithms (GA) to on-line identification of linear time-varying systems; a number of modifications are made to the Simple Genetic Algorithm to improve the performance of the algorithm in identification applications. The simulation results indicate that the method is not only capable of following the changing parameters of the system, but also has improved the identification accuracy compared with that using the least square method.
By applying genetic algorithms (GA) to on-line identification of linear time-varying systems; a number of modifications are made to the Simple Genetic Algorithm to improve the performance of the algorithm in identification applications. The simulation results indicate that the method is not only capable of following the changing parameters of the system, but also has improved the identification accuracy compared with that using the least square method.
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