Multivariable Process Identification for Robust Control

摘要

Multi-input multi-output (MIMO) process identification is studied, where thepurpose of identification is control system design. An identification procedure is presented by which one can estimate not only a nominal parametric process model, but also an upper bound of the model uncertainty (modelling errors) in the frequency domain. The basic steps of this method consist of high order model estimation and subsequent model reduction. One advantage is that, in this framework, fundamental problems such as input design and model structure selection can easily be solved. Another advantage of the method is numerical simplicity and reliability. The identified nominal model and the error bound can readily be used for robust control system analysis and design. A simulation example is given to illustrate the method.