Nonlinear nondynamic systems which can be modelled by a linear combination of nonlinear functions are considered. An algorithm, based on correlation techniques, is presented for reducing the number of terms in such a model to a fixed but arbitrary number, n. It is shown that when the model is a line
A grey-box modeling approach for the reduction of nonlinear systems
✍ Scribed by Reinout Romijn; Leyla Özkan; Siep Weiland; Jobert Ludlage; Wolfgang Marquardt
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 690 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0959-1524
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📜 SIMILAR VOLUMES
A simple, but fundamental, theorem is given on the extent to which a nonlinear system model can have its order reduced. EssentialIy, the result is that the order, or the dimension of the state space representation, cannot be reduced to, or below, the dimension of the system's attractor. Several exam
Numerical simulations of large nonlinear dynamical systems, especially over long-time intervals, may be computationally very expensive. Model reduction methods have been used in this context for a long time, usually projecting the dynamical system onto a sub-space of its phase space. Nonlinear Galer
decoupling is discussed. An equivalent linear controller for the algorithm is given for robust stability analysis. Some rules for choosing the tuning knobs of GPC/MRM from the robust stability point of view are established. The introduction of an observer, as in GPC, is extended to MIMO GPC/MRM, and