关键词: 多工况过程, 采样延时, 期望最大化（EM）算法, 参数估计

Abstract: Aiming at the data characters of multi-operating and sampling delay in real industrial process modeling, the linear parameter varying model is chosen to fit the multi-operating process. And the linear ARX model is selected as the local model structure. At the same time, the sampling time delay and data identity are taken as the hidden variables of the Expectation Maximization（EM） algorithm while calculating the Maximum Likelihood Estimation（MLE） function. Finally the parameters of local models are acquired and the local ARX models are incorporated into the integral LPV model through the Gaussian weighting function. The continuous stirring tank reactor and 3-stage high purity distillation column are selected as the simulation examples of multi-operating process. The process models are established and sampling time delay of the process data is estimated accurately at the same time. Simulation results show that the proposed method can practically cope well with the modeling of the multi-operating industrial processes.

Key words: multi-operating process, sampling delay, Expectation Maximization（EM） algorithm, parameter estimation