The paper proposes a finite series expansion to approximate general nonlinear dynamic models to arbitrary accuracy. The method produces an approximation of nonlinear dynamics in the form of an aggregation of linear models, weighted by unimodal basis functions, and results in a linear growth bound on the approximation error. Furthermore, the paper demonstrates that the proposed approximation satisfies the modeling assumptions for analysis based on linear matrix inequalities and hence widens the applicability of these techniques to the area of nonlinear control.

Volume Subject Area:
Dynamic Systems and Technology
Topics:
Modeling, Nonlinear systems, Approximation, Dynamic models, Errors, Linear matrix inequalities, Nonlinear dynamics
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