Neural Adaptive Singularity-Free Control by Backstepping for Uncertain Nonlinear Systems

  • Zhandong Yu
  • Qingchao Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)


An adaptive neural control approach based on backstepping is presented. Unmodelled dynamics or external disturbances are considered in the nonlinear models. Approximating nonlinear dynamic is one of the performances of multi-layer feedforward neural networks. By the Lyapunov’s stability theory, the NN weights are turned on-line with no prior training needed. An important feature of the presented approach is that by modifying a novel quasi-weighted Lyapunov function, the possible control singularity in the design of NN adaptive controller is avoided effectively. Finally, the approach is applied in CSTR system. The simulation result is given to demonstrate the feasibility and effectiveness of the proposed method.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zhandong Yu
    • 1
  • Qingchao Wang
    • 1
  1. 1.Astronautics SchoolHarbin Institute of TechnologyHarbinChina

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