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Using Artificial Neural Networks for Closed Loop Control of a Hydraulic Prosthesis for a Human Elbow

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Emerging Intelligent Computing Technology and Applications (ICIC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 304))

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Abstract

We address control of a hydraulic prosthesis for human elbow, a problem in which it is essential to obtain quick simulation results to appreciate the system dynamic. The forward kinematics problem for a prosthesis developed at Politecnico di Bari is solved using artificial neural networks as an effective and simple method to solve the problem in real time and limit computations. We show the method effectiveness designing two PID regulators that control the arm thanks to the neural computation of the forward kinematics.

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References

  1. Foglia, M.M., Valori, M.: A wired actuated elbow for human prosthesis. UPB Scientific Bullettin, Series D: Mechanical Engineering 73(2), 49–58 (2011)

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  2. Huang, X.G., He, G.P.: New and efficient method for the direct kinematic solution of the general planar Stewart platform. In: IEEE International Conference on Automation and Logistics, Shenyang, China, vol. 5 (2009)

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  3. Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. (1998)

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  4. Lee, H.S., Han, M.-C.: The estimation for forward kinematic solution of Stewart platform using the neural network. In: International Conference on Intelligent Robots and Systems, vol. 1, pp. 501–506 (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy

    Vitoantonio Bevilacqua, Mariagrazia Dotoli, Francesco Acciani & Giacomo Tattoli

  2. Dipartimento di Ingegneria Meccanica e Gestionale, Politecnico di Bari, Italy

    Mario Massimo Foglia & Marcello Valori

Authors
  1. Vitoantonio Bevilacqua
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  2. Mariagrazia Dotoli
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  3. Mario Massimo Foglia
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  4. Francesco Acciani
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  5. Giacomo Tattoli
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  6. Marcello Valori
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  3. Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, Kentucky, USA

    Xiang Zhang

  4. School of Electrical, Computer & Telecommunications Engineering, The University of Wollongong,, 2522, North Wollongong, NSW, Australia

    Prashan Premaratne

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© 2012 Springer-Verlag Berlin Heidelberg

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Bevilacqua, V., Dotoli, M., Foglia, M.M., Acciani, F., Tattoli, G., Valori, M. (2012). Using Artificial Neural Networks for Closed Loop Control of a Hydraulic Prosthesis for a Human Elbow. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_69

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  • DOI: https://doi.org/10.1007/978-3-642-31837-5_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31836-8

  • Online ISBN: 978-3-642-31837-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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