Chapter 6 - Uncertain state delay systems identification

Abstract

This chapter first presents the problems of state space model identification of multirate processes with unknown time delay. The aim is to identify a multirate state space model to approximate the parameter-varying time delay system. The identification problems are formulated under the framework of the expectation–maximization algorithm. Through introducing two hidden variables, a new expectation–maximization algorithm is derived to estimate the unknown model parameters and the time delays simultaneously. Then, it presents a moving horizon estimation approach for the multirate sampled-data system with unknown time delay sequence. In this work, a moving horizon estimation-based approach is developed to tackle these issues. Compared with the Kalman filter algorithm, the proposed approach can simultaneously estimate both the continuous states and discrete time delay sequence for dynamic systems.