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Identification of nonlinearly parameterized nonlinear models: application to mass balance systems

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4 Author(s)
Liu, Xiangbin ; State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China ; Ortega, R. ; Hongye Su ; Jian Chu

A new framework to design parameter estimators for nonlinearly parameterized systems is proposed in this paper. The key step is the construction of a monotone function, which explicitly depends on some of the estimator tuning parameters. Monotonicity-or the related property of convexity-have already been explored by several authors with monotonicity (or convexity) being a priori assumptions that are, usually, valid only on some region of state space. In our approach monotonicity is enforced by the designer, effectively becoming a synthesis tool. In order to dispose of degrees of freedom to render the function monotone we depart from standard (gradient or least-squares) estimators and adopt instead the recently introduced immersion and invariance approach for adaptation.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009