LPV Indirect Continuous-Time System Identification Through a Downsampled Subspace Approach

• Tipo: Capítulo ou Parte de Livro
• Data: 2011

Autores

P. Lopes dos Santos (Autor) FEUP; T-P Azevedo Perdicoúlis (Autor) Outra; José A. Ramos (Autor) Outra; Jorge Leite Martins de Carvalho (Autor) FEUP

Livro

Título: Linear Parameter-varying System Identification: New Developments And Trends

Páginas: 231-258

ISBN: 9789814355452

Editora: World Scientific Publishing Co.

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia de controlo

Outras Informações

Abstract (EN): The successive approximation Linear Parameter Varying systems subspace identification algorithm for discrete-time systems is based on a convergent sequence of linear time invariant deterministic stochastic state-space approximations. In this chapter, this method is modified to cope with continuous-time LPV state-space models. To do this, the LPV system is discretised, the discrete-time model is identified by the successive approximations algorithm and then converted to a continuous-time model. Since affine dependence is preserved only for fast sampling, a subspace downsampling approach is used to estimate the linear time invariant deterministic-stochastic state-space approximations. A second order simulation example, with complex poles, illustrates the effectiveness of the new algorithm.

Idioma: Inglês

Tipo (Avaliação Docente): Científica