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

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.