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

2019/05/24 by Manas Mejari, Mejari, Manas, Mihály Petreczky +1
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1905.10113

openalex publication_date 2019/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we present a realization and an identification algorithm for\nstochastic Linear Parameter-Varying State-Space Affine (LPV-SSA)\nrepresentations. The proposed realization algorithm combines the deterministic\nLPV input output to LPV state-space realization scheme based on correlation\nanalysis with a stochastic covariance realization algorithm. Based on this\nrealization algorithm, a computationally efficient and statistically consistent\nidentification algorithm is proposed to estimate the LPV model matrices, which\nare computed from the empirical covariance matrices of outputs, inputs and\nscheduling signal observations. The effectiveness of the proposed algorithm is\nshown via a numerical case study.\n

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