Adaptive Neural Network Control of Helicopters

  • Shuzhi Sam Ge
  • Keng-Peng Tee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


In this paper, we propose robust adaptive neural network (NN) control for helicopter systems by using the Implicit Function Theorem and the Mean Value Theorem, which are useful tools for handling nonlinear nonaffine systems. We focus on single-input single-output (SISO) helicopter systems, which are exemplified by certain single-channel modes of operation, such as vertical flight and pitch regulation, and also by special conditions under which the multiple channels become decoupled. It is shown that under the proposed NN control, the output tracking error converges to a small neighbourhood of the origin, while all closed loop signals are Semi-Globally Uniformly Ultimately Bounded (SGUUB).


Unmanned Helicopter Pitch Tracking Adaptive Output Feedback Adaptive Neural Network Control Output Tracking Error 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shuzhi Sam Ge
    • 1
  • Keng-Peng Tee
    • 1
  1. 1.Department of Electrical & Computer EngineeringNational University of SingaporeSingapore

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