Multiple Model LPV Approach to Identification of Nonlinear Dual-rate System with Random Time Delay

Abstract

This paper deals with the problem of nonlinear dual-rate system identification with random time delay. The proposed approach adopts the multiple modeling framework, and the global LPV model is represented by a combination of various local models weighted by a probability function. The considered structure of the local model is in a state space form, and the process has fast rate inputs and slow rate outputs with random time delay. The expectation maximization algorithm is utilized to formulate and solve the problem of interest. The parameters of the local models and the weighting functions are estimated simultaneously. The particle smoothing technique is adopted to handle the computation of expectation functions. The effectiveness of the proposed approach is further illustrated through a simulation example.