Dynamic structure neural network for stable adaptive control of nonlinear systems

  • Authors:
  • Jingye Lei

  • Affiliations:
  • College of Engineering, Honghe University, Yunnan, China

  • Venue:
  • ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
  • Year:
  • 2011

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Abstract

In this paper an adaptive control strategy based on neural network for a class of nonlinear system is analyzed. A simplified algorithm is presented with the technique in generalized predictive control theory and the gradient descent rule to accelerate learning and improve convergence. Taking the neural network as a model of the system, control signals are directly obtained by minimizing the cumulative differences between a setpoint and output of the model. The applicability in nonlinear system is demonstrated by simulation experiments.