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Identification of linear parameter-varying systems via LFTs

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2 Author(s)
L. H. Lee ; Dept. of Mech. Eng., California Univ., Berkeley, CA, USA ; K. Poolla

This paper considers the identification of linear parameter-varying (LPV) systems having linear-fractional parameter dependence. We present a natural prediction error method, using gradient- and Hessian-based nonlinear optimization algorithms to minimize the cost function. Computing the gradients and (approximate) Hessians is shown to reduce to simulating LPV systems and computing inner products. Issues relating to initialization and identifiability are discussed. The algorithms are demonstrated on a numerical example

Published in:

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on  (Volume:2 )

Date of Conference:

11-13 Dec 1996