This chapter presents an overview of the available methods for identifying input-output LPV models both in discrete time and continuous time with the main focus on noise modeling issues. First, a least-squares approach and an instrumental variable method are presented for dealing with LPV-ARX models. Then, a refined instrumental variable approach is discussed to address more sophisticated noise models like Box-Jenkins in the LPV context. This latter approach is also introduced in continuous time and efficient solutions are proposed for both the problem of time-derivative approximation and the issue of continuous-time modeling of the noise.
|Title of host publication||Linear parameter-varying system identification: new developments and trends|
|Editors||P.L. Santos, dos, T.P.A. Perdicoúlis, C. Novara, J. A. Ramos, D. E. Rivera|
|Place of Publication||Singapore|
|Number of pages||381|
|Publication status||Published - 2011|
|Name||Advanced Series in Electrical and Computer Engineering|