Volterra-type models for nonlinear systems identification

CHRISTIAN SCHMIDT; SILVINA INES BIAGIOLA; JUAN EDMUNDO COUSSEAU; JOSE LUIS FIGUEROA

San Carlos de Bariloche

Congreso; XV Reunión de trabajo en Procesamiento de la Información y Control; 2013

Universidad Nacionel de Río Negro

In this work, multi-input multioutput (MIMO) nonlinear process identification is dealt with. In particular, two Volterra-type models are discussed in the context of system identification. These models are: Memory Polynomial (MP) and Modified 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 models sets with low parameters complexity. Simulation example is given to illustrate the quality of the obtained models.