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Nearly Optimal Control for Nonlinear Systems with Dead-Zone Control Input Based on the Iterative ADP Approach

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7663)

Abstract

This paper focuses on a class of unknown discrete-time nonlinear systems with dead-zone control constraints based on adaptive dynamic programming (ADP). The discrete-time Hamilton-Jacobi-Bellman (DTHJB) equation corresponding to the dead-zone control input is formulated. Based on ADP technique, a new cost function is proposed that solves the optimal control with dead zone constraints effectively. It shows that this algorithm allows the implementation of the optimal control without knowing nonlinear affine system model and dead-zone dynamics. Finally, a simulation example is provided to verify the effectiveness of the proposed iterative algorithm.

Keywords

  • DTHJB
  • dead-zone
  • adaptive dynamic programming
  • nonlinear systems
  • neural networks

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Zhang, D., Liu, D., Wei, Q. (2012). Nearly Optimal Control for Nonlinear Systems with Dead-Zone Control Input Based on the Iterative ADP Approach. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34475-6_16

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  • DOI: https://doi.org/10.1007/978-3-642-34475-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34474-9

  • Online ISBN: 978-3-642-34475-6

  • eBook Packages: Computer ScienceComputer Science (R0)