System Identification for Multivariable Control

摘要

System identification methods and modern control theory are applied to industrial processes. These processes must often be controlled in order to meet certain requirements with respect to the product quality, safety, energy consumption, and environmental load. Modern control system design methods which take the occurring interaction phenomena and stochastic disturbances into account are used. An accurate dynamic mathematical model of the process, by theoretical modelling and/or by system identification is obtained. The computational aspects of two important types of identifications methods, i.e., stochastic realization and prediction error based parameter estimation are studied. The studied computational aspects are the robustness, the accuracy, and the computational costs of the methods. Theoretical analyses and applications to a multivariable pilot scale process, operating under closed loop conditions are investigated.