Control relevant identification for robust optimal control

Authors:
Nata K. Dinata;William R. Cluett
Affiliations:
Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ont., Canada M5S 3E5;Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ont., Canada M5S 3E5
Venue:
Automatica (Journal of IFAC)
Year:
2005

Citing 9
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Abstract

This paper presents an approach to designing the input signal for an identification experiment, in which the process model estimate is to be used to formulate and solve for a robust (in a worst case sense) optimal controller. The input signal is designed to contain the information that is relevant for the end use of the model, that is for control purposes. The proposed approach uses sensitivity analysis to determine the input signal frequencies that are important with respect to a certain measure of achievable controller performance in conjunction with a frequency sampling filter model of the process. Based on the sensitivity analysis, an iterative experimental design methodology is suggested.