Realization and identification algorithm for stochastic LPV state-space models with exogenous inputs

被引：2

作者：

Mejari, Manas ^{[1
]}

Petreczky, Mihaly ^{[2
]}

机构：

[1] IDSIA Dalle Molle Inst Artificial Intelligence SU, CH-6928 Manno, Switzerland

[2] Ecole Cent Lille, Ctr Rech Informat Signal & Automat Lille, UMR CNRS 9189, F-59651 Villeneuve Dascq, France

来源：

IFAC PAPERSONLINE | 2019年 / 52卷 / 28期

关键词：

SUBSPACE IDENTIFICATION; BILINEAR-SYSTEMS;

D O I：

10.1016/j.ifacol.2019.12.340

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a realization and an identification algorithm for stochastic Linear Parameter-Varying State-Space Affine (LPV-SSA) representations. The proposed realization algorithm combines the deterministic LPV input output to LPV state-space realization scheme based on correlation analysis with a stochastic covariance realization algorithm. Based on this realization algorithm, a computationally efficient and statistically consistent identification algorithm is proposed to estimate the LPV model matrices, which are computed from the empirical covariance matrices of outputs, inputs and scheduling signal observations. The effectiveness of the proposed algorithm is shown via a numerical case study. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：13 / 19

页数：7

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