INVESTIGADORES
SCHMIDT Christian Andres
artículos
Título:
Volterra-type models for nonlinear systems identification
Autor/es:
C. SCHMIDT; S. BIAGIOLA; J. E. COUSSEAU; J. L. FIGUEROA
Revista:
APPLIED MATHEMATICAL MODELLING
Editorial:
ELSEVIER SCIENCE INC
Referencias:
Lugar: Amsterdam; Año: 2013
ISSN:
0307-904X
Resumen:
In this work, multi-input multi-output (MIMO) nonlinear process identication is dealt with. In particular, two Volterra-type models are discussed in the context of system identication. These models are: Memory Polynomial (MP) and Modied Generalized Memory Polynomial (MGMP), which can be considered as a generalization of Hammerstein and Wiener models, respectively. Both of them are appealing representations as they allow to describe larger model sets with less parametric complexity. Simulation example is given to illustrate the quality of the obtained models.
