Identification, Estimation and Control of Continuous-Time Systems Described by Delta Operator Models

Abstract

This Chapter outlines a unified approach to the identification, estimation and control of linear, continuous-time, stochastic, dynamic systems which can be described by delta (δ) operator models with constant or time-variable parameters. It shows how recursive refined instrumental variable estimation algorithms can prove effective both in off-line model identification and estimation, and in the implementation of self-tuning or self-adaptive True Digital Control (TDC) systems which exploit a special Non-Minimum State Space (NMSS) formulation of the δ operator models.