DocumentCode :
2344872
Title :
FPGA Design and Implementation Issues of Artificial Neural Network Based PID Controllers
Author :
Gupta, Vikas ; Khare, K. ; Singh, R.P.
Author_Institution :
Dept. of Electron. & Telecommun., Vidyavardhani´´s Coll. of Eng., Thane, India
fYear :
2009
fDate :
27-28 Oct. 2009
Firstpage :
860
Lastpage :
862
Abstract :
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 of 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.
Keywords :
backpropagation; field programmable gate arrays; integrated circuit design; neural nets; reconfigurable architectures; three-term control; FPGA design; PID controller; artificial neural network; backpropagation neural network; error self-recurrent neural network; multiinput neuron; nonlinear excitation function; reconfigurable computing architecture; Artificial neural networks; Communication system control; Computer networks; Control systems; Field programmable gate arrays; Hardware; Multi-layer neural network; Neural networks; Neurons; Three-term control; FPGA; PID controller; artificial neural networks; error self-recurrent neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
Conference_Location :
Kottayam, Kerala
Print_ISBN :
978-1-4244-5104-3
Electronic_ISBN :
978-0-7695-3845-7
Type :
conf
DOI :
10.1109/ARTCom.2009.182
Filename :
5328349
Link To Document :
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