M.Sc Thesis

M.Sc StudentGrouzman Leonid
SubjectIdentification Based Power Station Models for Purposes of
Robust Control Design
DepartmentDepartment of Electrical and Computer Engineering
Supervisors PROFESSOR EMERITUS Ezra Zeheb
DR. Roland Kulessky


The thesis is concerned with creating a basis for the design of robust controllers, which pertain, in particular, to power station processes. The basis is carried with the help of a known two staged identification method. The purpose of the identification method is to provide, in addition to the usual nominal model, a set of interval models which represents the uncertainties of the identified models. This should be a pertinent basis for designing robust controllers under uncertainty conditions.

The main idea is identification of SISO models family using a number of data subsets, which are selected from the whole data set by a special procedure. According to predefined criteria nominal and uncertainty models are calculated from this models family. For exact calculation of maximal frequency range, in which a model correctly describes the process, a model transfer function is represented by transfer function with interval coefficients. A possible method for calculation of such interval coefficients is proposed. The maximal frequency range test is based on calculating frequency response envelopes for such ”interval” model by the analytical method [26]. The method of calculation of common maximal frequency range (where both nominal and uncertainty models correctly describe the process) is proposed.

In addition, the problem of improving identification accuracy for a differentiating process is solved. Adaptive prefiltering of data is considered as a possible solution. Suitable scheme for searching variable filter parameter is presented by using the proposed criterion. Main theoretical results are illustrated by practical applications at the Israel Electric Corporation.