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In this paper, we present a realization and an identification algorithm forstochastic Linear Parameter-Varying State-Space Affine (LPV-SSA)representations. The proposed realization algorithm combines the deterministicLPV input output to LPV state-space realization scheme based on correlationanalysis with a stochastic covariance realization algorithm. Based on thisrealization algorithm, a computationally efficient and statistically consistentidentification algorithm is proposed to estimate the LPV model matrices, whichare computed from the empirical covariance matrices of outputs, inputs andscheduling signal observations. The effectiveness of the proposed algorithm isshown via a numerical case study.

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