Where academic tradition
meets the exciting future

You are here: TUCS > PUBLICATIONS > Publication Search > Bayesian Statistical Analysis ...

Bayesian Statistical Analysis for Performance Evaluation in Real-Time Control Systems

Pontus Boström, Mikko Heikkilä, Mikko Huova, Marina Waldén, Matti Linjama, Bayesian Statistical Analysis for Performance Evaluation in Real-Time Control Systems. TUCS Technical Reports 1136, TUCS, 2015.

Abstract:

This paper presents a method for statistical analysis of hybrid systems affected by stochastic disturbances, such as random computation and communication delays. The method is applied to the analysis of a computer controlled digital hydraulic power management systems, where such effects are present. Bayesian inference is used to perform parameter estimation and we use hypothesis testing based on Bayes factors to compare properties of different variants of the system to assess the impact of different random disturbances. The key idea is to use sequential sampling to generate only as many samples from the models as needed to achieve desired confidence in the result.

Files:

Full publication in PDF-format

BibTeX entry:

@TECHREPORT{tBoHeHuWaLi15a,
  title = {Bayesian Statistical Analysis for Performance Evaluation in Real-Time Control Systems},
  author = {Boström, Pontus and Heikkilä, Mikko and Huova, Mikko and Waldén, Marina and Linjama, Matti},
  number = {1136},
  series = {TUCS Technical Reports},
  publisher = {TUCS},
  year = {2015},
}

Belongs to TUCS Research Unit(s): Distributed Systems Laboratory (DS Lab)

Edit publication