International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Saturation Compensation of a DC Motor System Using Neural Networks

  • Jang, Jun-Oh (Department of Computer Control Engineering, Uiduk University) ;
  • Ahn, Ihn-Seok (Department of Computer Control Engineering, Uiduk University)
  • Published : 2005.06.01
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Abstract

A neural networks (NN) saturation compensation scheme for DC motor systems is presented. The scheme that leads to stability, command following and disturbance rejection is rigorously proved. On-line weights tuning law, the overall closed loop performance and the boundness of the NN weights are derived and guaranteed based on Lyapunov approach. The simulation and experimental results show that the proposed scheme effectively compensate for saturation nonlinearity in the presence of system uncertainty.

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References

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