FPGA Design and Implementation Issues of Artificial Neural Network Based PID Controllers

被引：4
|
作者：
Gupta, Vikas [1 ]
Khare, K. [2 ]
Singh, R. P. [2 ]
机构：
[1] Vidyavardhanis Coll Engn, Dept Elect & Telecommun, Vasai Rd W, Thana, India
[2] MAULANA Azad Natl Inst Technol, Dept Elect & Commun, Bhopal, India
来源：
2009 INTERNATIONAL CONFERENCE ON ADVANCES IN RECENT TECHNOLOGIES IN COMMUNICATION AND COMPUTING (ARTCOM 2009) | 2009年
关键词：
FPGA; PID controller; artificial neural networks; error self-recurrent neural networks;
D O I：
10.1109/ARTCom.2009.182
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper discusses implementation issues of FPGA and ANN based PID controllers. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation or a multi-input neuron with linear/nonlinear excitation functions using FPGA. It also suggests advantages of error self-recurrent neural networks over back propagation neural network.
引用
收藏
页码：860 / +
页数：2
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