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Neuro-Optimal Controller for Robot Manipulators

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Artificial Neural Networks and Machine Learning – ICANN 2013 (ICANN 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8131))

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Abstract

This paper presents an algorithm for continuous-time quadratic optimization with neural compensation of motion control. A simpler reformulation explicit solution to the Hamilton-Jacobi-Bellman equation for optimal control of rigid robot motion is found by solving an algebraic Riccati matrix equation. The system stability is investigated according to Lyapunov function theory and it is shown that global asymptotic stability holds in the case of known system model. It is also shown how optimal control and neural control may act in concert in the case of unknown system model. The neural algorithm is derived from Lyapunov stability analysis, so that both system-tracking stability and error convergence can be guaranteed in the closed-loop system. Experimental and simulation results from a two-link robot manipulator show the satisfactory performance of the proposed control scheme.

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References

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Author information

Authors and Affiliations

  1. Department of Electronics, Jijel University, 98 Ouled Aissa, Jijel, 18000, Algeria

    Mohammed Boukens & Abdelkrim Boukabou

Authors
  1. Mohammed Boukens
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  2. Abdelkrim Boukabou
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Editor information

Editors and Affiliations

  1. Faculty Automation,, Technical University of Sofia, 8 St. Kl. Ohridski Blvd., 1000, Sofia, Bulgaria

    Valeri Mladenov

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.25A, 1113, Sofia, Bulgaria

    Petia Koprinkova-Hristova

  3. Institute of Neural Information Processing, University of Ulm, 89075, Ulm, Germany

    Günther Palm

  4. Quartier UNIL-Dorigny, Bâtiment Internef, Université de Lausanne, 1015, Lausanne, Switzerland

    Alessandro E. P. Villa

  5. Department of Computer Science, University of Milano, Via Comelico, 39, 20135, Milano, Italy

    Bruno Appollini

  6. Knowledge Engineering, School of Computing and Mathematical Sciences, Auckland University of Technology, 120 Mayoral Drive, 3rd floor, 1010, Auckland, New Zealand

    Nikola Kasabov

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© 2013 Springer-Verlag Berlin Heidelberg

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Boukens, M., Boukabou, A. (2013). Neuro-Optimal Controller for Robot Manipulators. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_63

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  • DOI: https://doi.org/10.1007/978-3-642-40728-4_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40727-7

  • Online ISBN: 978-3-642-40728-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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