Neural Network Control Based on Optimization of Immune Genetic Algorithm for Heat Tunnel of Fire Detector

Author

Bu, Yunfeng ; Shen, Yi

Author_Institution

Dept. of Mech. Eng., Huaiyin Inst. of Technol., Huaiyin

fYear

2008

fDate

1-3 Nov. 2008

Firstpage

47

Lastpage

50

Abstract

To realize the adaptive control in the heat tunnel system of fire detector, an adaptive PID control algorithm based on BP network and immune genetic algorithm (IGA) is presented. Firstly, the immune genetic algorithm is used to optimize the weights of BP network, which reduces the influence of control effect due to initial network weights; secondly, the PID parameters are adjusted on line based on the BP network during the control of heat tunnel. Experiment results show that this control algorithm is effective. Compared to other algorithms, the proposed algorithm owns high control precision, suppression capacity to noise and disturbance, and strong robustness.

Keywords

adaptive control; backpropagation; delays; fires; genetic algorithms; heat systems; neurocontrollers; nonlinear control systems; three-term control; tunnels; adaptive PID control algorithm; backpropagation network; delay; fire detector; heat tunnel system; immune genetic algorithm optimization; large lag system; neural network control; nonlinear system; Adaptive control; Control systems; Detectors; Fires; Genetic algorithms; Neural networks; Noise robustness; Programmable control; Temperature control; Three-term control; heat tunnel; immune genetic algorithm; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3391-9

Electronic_ISBN

978-0-7695-3391-9

Type

conf

DOI

10.1109/ICINIS.2008.50

Filename

4683165