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논문검색

Networked Control System Based on RBF Neural Network

원문정보

초록

영어

In the networked control system, the control interference, measurement noise and time delay make traditional digital PID algorithm not reach stable state. On the basis of simple digital PID algorithm, Kalman filter is first introduced, the effect of the interference and noise is decreased, and stability is improved. Then RBF (Radial Basis Function) neural network is used, Jacobian array is computed, the three parameters of PID algorithm are adjusted. Furthermore, the resistance integral saturation is used to limit the size of control quantity. Finally the simulation research on a DC (Direct Current) motor is done, and the simulation results show the effectiveness of the proposed algorithm when time delay, noise and interference are all large.

목차

Abstract
 1. Introduction
 2. System Model
 3. Proposed Control Algorithm
  3.1. PID controller and its deficiencies
  3.2. PID Controller Based on RBF Neural Network
  3.3. RBF Neural Network
  3.4. Kalman filter
  3.5. Resistance integral saturation
 4. Simulation
 References

저자정보

  • Haitao Zhang Electronic and Information Engineering College, Henan University of Science and Technology
  • Jinbo Hu Electronic and Information Engineering College, Henan University of Science and Technology
  • Wenshao Bu Electronic and Information Engineering College, Henan University of Science and Technology

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