Qing Li, Deling Zheng, and Jianlong Zhou, Stabilization of Chaotic Time Series by Proportional Pulse in the System Variable Based on Genetic Algorithm, J. Univ. Sci. Technol. Beijing, 6(1999), No. 3, pp. 228-229.
Cite this article as:
Qing Li, Deling Zheng, and Jianlong Zhou, Stabilization of Chaotic Time Series by Proportional Pulse in the System Variable Based on Genetic Algorithm, J. Univ. Sci. Technol. Beijing, 6(1999), No. 3, pp. 228-229.
Qing Li, Deling Zheng, and Jianlong Zhou, Stabilization of Chaotic Time Series by Proportional Pulse in the System Variable Based on Genetic Algorithm, J. Univ. Sci. Technol. Beijing, 6(1999), No. 3, pp. 228-229.
Citation:
Qing Li, Deling Zheng, and Jianlong Zhou, Stabilization of Chaotic Time Series by Proportional Pulse in the System Variable Based on Genetic Algorithm, J. Univ. Sci. Technol. Beijing, 6(1999), No. 3, pp. 228-229.
Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China
Handan iron and Steel Co., Handan 056015, China
中文摘要
The PPSV (Proportional Pulse in the System Variable) algorithm is a convenient method for the stabilization of the chaotic time series. It does not require any previous knowledge of the system. The PPSV method also has a shortcoming, that is, the determination off. is a procedure by trial and error, since it lacks of optimization. In order to overcome the blindness, GA (Genetic Algorithm), a search algorithm based on the mechanics of natural selection and natural genetics, is used to optimize the λi The new method is named as GAPPSV algorithm. The simulation results show that GAPPSV algorithm is very efficient because the control process is short and the steady-state error is small.
The PPSV (Proportional Pulse in the System Variable) algorithm is a convenient method for the stabilization of the chaotic time series. It does not require any previous knowledge of the system. The PPSV method also has a shortcoming, that is, the determination off. is a procedure by trial and error, since it lacks of optimization. In order to overcome the blindness, GA (Genetic Algorithm), a search algorithm based on the mechanics of natural selection and natural genetics, is used to optimize the λi The new method is named as GAPPSV algorithm. The simulation results show that GAPPSV algorithm is very efficient because the control process is short and the steady-state error is small.
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