Study of Soft-sensing Method Based on PSO-SVM for Key Bio Parameters

Some key biological parameters in the process of microorganism fermentation are difficult to measure online and real-time,which greatly affects the optimization of control system in fermentation.In order to solve the problem of measurement,this paper used a soft-sensing method based on PSO-SVM.The optimal parameters of support vector machines(SVM)were optimized by the algorithm of particle swarm optimization(PSO).Meanwhile,the soft-sensing model based on PSO-SVM was established.Then the soft-sensing model was verified by simulation according to Lysine fermentation data,the simulation results show that the model has good learning precision and generalization ability.The modeling time of PSO-SVM algorithm is far less than that of SVM.