Online Bayesian system identification in multivariate autoregressive models via message passing

2025/06/03 by T. N. Nisslbeck, Nisslbeck, T. N., Wouter M. Kouw +1 · 1 citation
Engineering · Computer Science · #Control Systems and Identification #Fault Detection and Control Systems #Gaussian Processes and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.2506.02710

Abstract

We propose a recursive Bayesian estimation procedure for multivariate autoregressive models with exogenous inputs based on message passing in a factor graph. Unlike recursive least-squares, our method produces full posterior distributions for both the autoregressive coefficients and noise precision. The uncertainties regarding these estimates propagate into the uncertainties on predictions for future system outputs, and support online model evidence calculations. We demonstrate convergence empirically on a synthetic autoregressive system and competitive performance on a double mass-spring-damper system.

Citations

• Coupled autoregressive active inference agents for control of multi-joint dynamical systems
• Reactive Message Passing for Scalable Bayesian Inference
• Bayesian Experimental Design: A Review

Cited by

• Message passing-based inference in an autoregressive active inference agent

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