Real-time reconfigurable micro-system based on FPGA and CPLD for dual-mode PID control through backpropagation neural network

Author

Ruan, Zhuo ; Han, Yuzhang ; Han, Jianguo

Author_Institution

Dept. of Electr. Eng., Beijing Univ. of Chem. Technol.

fYear

0

fDate

0-0 0

Lastpage

5

Abstract

In this paper, a practically usable dual-mode control micro-system based on CPLD and reconfigurable FPGA is described. FPGA can be dynamically reconfigured under the control of CPLD to implement two models, backpropagation neural network model and its training model, both of which are respectively directed to two control modes for industrial produce. One mode is neural network performed automatic control, the other one as human-interfered traditional control. That is, only one single FPGA is reconfigured with multifunction. This technique can be widely applied into other control fields such as the adaptive control in different environments, space-ship control, measuring control in rough situation, and even production control

Keywords

adaptive control; backpropagation; field programmable gate arrays; neural chips; neurocontrollers; three-term control; CPLD; FPGA; adaptive control; backpropagation neural network; dual-mode PID control; human-interfered traditional control; real-time reconfigurable microsystem; Automatic control; Backpropagation; Control systems; Field programmable gate arrays; Industrial control; Industrial training; Neural networks; Real time systems; Reconfigurable logic; Three-term control; BP Neural Network; Dynamically Reconfigurable; dual-mode (human interfered traditional control and neural network performed control); real-time;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Control Applications, 2005. ICIECA 2005. International Conference on

Conference_Location

Quito

Print_ISBN

0-7803-9419-4

Type

conf

DOI

10.1109/ICIECA.2005.1644343

Filename

1644343