Identification and Control based on Neural Networks and Ant Colony Optimization Algorithm

被引:0
|
作者
Xu, Qiang [1 ]
Lin, Jihai [1 ]
Yang, Jia [2 ]
机构
[1] Chongqing Technol & Business Univ, Coll Comp Sci & Informat Engn, Chongqing 400067, Peoples R China
[2] Chongqing Univ Technol, Coll Elect & Informat Automat, Masuho, Yamanashi 4000502, Japan
关键词
Large Delay Time System; Identification of Delay Time; Prediction Model; Ant Colony Optimization Algorithm;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
It is difficult to have good performance to control large delay time system. A neural network identification method for nonlinear system's delay time was discussed. Using the abrupt mutation resulted from the training error sum square of the real output and the expected output of the network, this method changed the input sample period of the neural network so that it could discriminate the delay time of the nonlinear model. Combining the discrimination of neural network system with long time delay and the control method based on model prediction, searching PID controller parameters based on ant colony optimization algorithm, it was applied to control boiler combustion system. The simulation results show that this scheme has much better advantage of celerity and robustness.
引用
收藏
页码:1255 / +
页数:2
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