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Adaptive Inverse Control Method Based on SVM-Fuzzy Rules Acquisition System for Twin-Lift Spreader System

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Electrical, Information Engineering and Mechatronics 2011

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 138))

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Abstract

This paper proposes a new method of adaptive inverse control based on Support Vector Machine-Fuzzy Rules Acquisition System (SVM-FRAS) for twin-lift spreaders. In this control mechanism, an identifier is established based on SVM-FRAS, and an inverse controller based on SVM-FRAS is designed. The proposed adaptive inverse control method can automatically extract control rules from the process data. Comprehensibility is one of the required characteristics for a complex twin-lift spreader. We use the proposed SVM-FRAS-based adaptive inverse control method to obtain the rule-based process and the control model of the twin-lift spreader. Based on the simulation experiments for twin-lift spreaders, the SVM-FRAS adaptive inverse control method is found to be effective.

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References

  1. Smola AJ, Scholkopf B (2004) A tutorial on support vector regression. Stat Comput 14:199–222

    Article  MathSciNet  Google Scholar 

  2. Mittul S, Jivitej C, Puneet A, Suresh C (2011) Reduced twin support vector regression. Neurocomputing 74:1474–1477

    Article  Google Scholar 

  3. Huang XX, Shi FH, Gu W, Chen SB (2009) SVM-based fuzzy rules acquisition system for pulsed GTAW process. Eng Appl Artif Intel 22:1245–1255

    Article  Google Scholar 

  4. Huang XX, Gu W, Shi FH, Chen SB (2009) An adaptive inverse control method based on SVM-fuzzy rules acquisition system for pulsed GTAW process. Int J Adv Manuf Technol 44:686–694

    Article  Google Scholar 

  5. Widrow B, Walach EW (1996) Adaptive inverse control. Prentice-Hall, Upper Saddle River

    Google Scholar 

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Acknowledgments

This work is supported by Shanghai Leading Academic Discipline Project (S30602), National High-tech R&D Program of China (863 Program) by Ministry of Science & Technology of China (No. 2009AA043000) and National Natural Science Foundation of China (No. 60805018).

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Correspondence to Xixia Huang .

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© 2012 Springer-Verlag London Limited

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Huang, X., Shi, F., Zhang, H. (2012). Adaptive Inverse Control Method Based on SVM-Fuzzy Rules Acquisition System for Twin-Lift Spreader System. 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_8

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  • DOI: https://doi.org/10.1007/978-1-4471-2467-2_8

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2466-5

  • Online ISBN: 978-1-4471-2467-2

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