Reliable Robust Controller Design for Nonlinear State-Delayed Systems Based on Neural Networks

  • Yanjun Shen
  • Hui Yu
  • Jigui Jian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)


An approach is investigated for the adaptive guaranteed cost control design for a class of nonlinear state-delayed systems. The nonlinear term is approximated by a linearly parameterized neural networks(LPNN). A linear state feedback H  ∞  control law is presented. An adaptive weight adjustment mechanism for the neural networks is developed to ensure H  ∞  regulation performance. It is shown that the control gain matrices and be transformed into a standard linear matrix inequality problem and solved via a developed recurrent neural network.


Neural Network Wavelet Network Multilayer Neural Network State Space Approach Linear State Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yanjun Shen
    • 1
  • Hui Yu
    • 1
  • Jigui Jian
    • 1
  1. 1.Institute of Nonlinear Complex system, College of ScienceThree Gorges UniversityYichang, HuibeiChina

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