Volterra-type models for nonlinear systems identification

被引:15
|
作者
Schmidt, C. A. [1 ]
Biagiola, S. I. [1 ]
Cousseau, J. E. [1 ]
Figueroa, J. L. [1 ]
机构
[1] Univ Nacl Sur, CONICET, Inst Invest Ingn Elect, RA-8000 Bahia Blanca, Buenos Aires, Argentina
关键词
Nonlinear identification; Volterra-type models; Wiener model; Hammerstein model; MEMORY;
D O I
10.1016/j.apm.2013.10.041
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this work, multi-input multi-output (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 model sets with less parametric complexity. Simulation example is given to illustrate the quality of the obtained models. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:2414 / 2421
页数:8
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