Abstract
To describe the lateral jet force model accurately, an identification method based on FCM–SVM is provided. The experimental data is clustered with this method to gain the best partition and separating hyperplanes. Different classes are identified respectively using maximum-likelihood estimation method. The test data is classified through separating hyperplanes. The output of test data can be forecasted according to the expression of corresponding class. Result shows that the precision is increased by 31% compared with traditional identification model. The identification result based on FCM–SVM can supply support for the design of control system.
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Acknowledgments
The authors thanks Beijing Simulation Center for their support and for providing data used in this work. The author also thanks the financial support of science and technology on space system simulation laboratory fund item of china.
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© 2012 Springer-Verlag London Limited
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Liu, X., Dong, Y., Wang, X. (2012). Lateral Jet Force Model Identification Based on FCM–SVM. In: Wang, X., Wang, F., Zhong, S. (eds) Electrical, Information Engineering and Mechatronics 2011. Lecture Notes in Electrical Engineering, vol 138. Springer, London. https://doi.org/10.1007/978-1-4471-2467-2_42
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DOI: https://doi.org/10.1007/978-1-4471-2467-2_42
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