Dynamic Modeling Approach Based on Improved PSO and FLANN for Sensor
Zhang YuanYuan1，2,Xu KeJun3，4,Xu Yaohua2
1, School of Instrument Science and Photoelectric Engineering, Hefei University of Technology, Hefei 230009
2,School of Electronic Science and Technology, Anhui University, Hefei 230039
3，School of Electrical and Automation Engineering ,Hefei University of Technology ,Hefei 230009
4，Engineering Technology Research Center of Industrial Automation, Anhui Province, Hefei 230009)
In this paper, the dynamic linear model of sensor is founded based on the improved particle swarm optimization (PSO) algorithm and function link artificial neural network (FLANN). According to measurement data in dynamic calibration ,the weights of network is used to initialize one particle station of whole particel swarm when the training of FLANN has finished.Then the improved PSO algorithm is applied ,the global best particle station of particle swarm is the coefficient of sensor’s dynamic model what we need. The experiment results show that this approach has excellence of both PSO and FLANN, meanwhile it has better precision.
2009, Vol. 28 
