Hierarchical multiple model identification for complex objects

In order to solve the modeling problem of complex objects with jump parameters, a hierarchical multiple model online identification method based on mechanism of antigen identification was proposed. In this paper, through training the input-output data the model set was acquired to act as a classifier to divide the uncertain space of parameters into several small subspaces. In these subspaces, the RLS algorithm was employed to identify the precise parameters online. The algorithm training model set and the procedure of online identification were presented. The method combined the advantages of prior knowledge and online training. Its simulation on identification for a industry process with jump operating mode was carried out. Results showed the method has good identification performance for the objects with jump parameters.