Optimization Algorithm on Intelligent Control System

نویسندگان

  • Peng Li
  • Zengxiu Zhang
  • Xufeng An
چکیده

A kind of intelligent control system based on fuzzy neural network optimized and trained by the adaptive ant colony optimization algorithm was proposed and constructed in this paper. The structure and the parameters of this intelligent control system were introduced. This intelligent control system used as joint servo controller is applied to the simulation research of robot control. Simulation has been carried out to evaluate the performance of proposed method and to compare the performance with optimization by conventional ant colony algorithm. The results show that the performance of trajectory tracking and the precision of robot control can be improved and have quick convergence based on adaptive ant colony algorithm in the training. This intelligent control method also has a good application prospects in other related fields. Copyright © 2013 IFSA.

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تاریخ انتشار 2013