Soft Sensing Modeling Based on Dynamic Fuzzy Neural Network for Penicillin Fermentation
Since the establishment of initial model and determination of the rules’ number of traditional fuzzy neural network both rely on experiential knowledge, so a soft sensor modeling method using dynamic fuzzy neural network is proposed in this paper. The network structure is based on extended radial basis function neural network. Sequential learning method is utilized for parameter estimation and structure identification, and then the pruning technique is introduced to make the structure more compact. The network structure identification is equivalent to determination of fuzzy rules. And the auxiliary variables are identified by uniform incidence degree algorithm. Take the key biological parameters soft sensing of penicillin fermentation process as an example, the simulation results show that this proposed method has satisfied modeling precision and practicality.
Dynamic Fuzzy Neural Network Soft Sensing Uniform Incidence Degree Modeling
HUANG Yonghong CHENG Hao HUANG Li SUN Lina
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang ,China,210013
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
3383-3388
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）