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Citation: Wei Dong, Ma Ruiping, Zhang Minglian, et al. Artificial-neural-network-based nonlinear adaptive control and simulation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(03): 217-221. (in Chinese)

Artificial-neural-network-based nonlinear adaptive control and simulation

  • Received Date: 04 Nov 2002
  • Publish Date: 31 Mar 2004
  • The increasing complexity of the nonlinear systems highlights the need for advanced modeling and control techniques for effective control. An artificial-neural-network-based nonlinear adaptive control system was studied, which identified the dynamics of the plant with improved NARMA(nonlinear auto-regressive moving average) model at first. Then, the control algorithm was deduced with respect to the model directly. An adaptive system was designed to control a longitudinal missile autopilot which achieves tracking of external reference commands in angle of attack.Simulation results illustrate the ability of this technique to compensate for unmodeled dynamics and uncertain plant nonlinearities.

     

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