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논문검색

RBF Neural Network Controller Research Based on AFSA Algorithm

초록

영어

Artificial fish-swarm algorithm is a realization model of the swarm intelligence optimization algorithm. It uses the optimization model of imitated nature fish for feeding from top to bottom, clusters and rear, local optimization by individual fish, achieve the purpose of global optimal values highlighted in the groups. RBFNN based on the AFSA can accurately find the optimal solution quickly and ensure the diversity of artificial fish. It is easier to find the global optimal point of optimal fish. This design uses second-order pendulum as a controlled object, using artificial fish swarm algorithm applied to the neural network training algorithms, building design of RBF Neural networks control module , verifing by Matlab simulation of actual control controller performance.

목차

Abstract
 1. Introduction
 2. The Basic Theory:
 3. RBF Neural Network Artificial Fish Swarm Algorithm:
 4. Experimental Results and Simulation
 5. Conclusion
 References

저자정보

  • Qing-kun Song School of Automation Harbin University of Science And Technology Control theory and control engineering
  • Meng-meng Xu School of Automation Harbin University of Science And Technology Control theory and control engineering
  • Yi Liu School of Automation Harbin University of Science And Technology Control theory and control engineering

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