A Bayesian approach to modeling the conditional density of the inverse controller

Randa Herzallah, David Lowe

Research output: Chapter in Book/Published conference outputConference publication

Abstract

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems. For illustration purposes, the proposed methodology is applied to linear Gaussian systems.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Control Applications, 2004
PublisherIEEE
Pages788-793
Number of pages6
Volume1
ISBN (Print)0-7803-8633-7
DOIs
Publication statusPublished - 2004
Event2004 IEEE International Conference on Control Applications - Taipei, United Kingdom
Duration: 2 Sep 20044 Sep 2004

Conference

Conference2004 IEEE International Conference on Control Applications
CountryUnited Kingdom
CityTaipei
Period2/09/044/09/04

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