Probabilistic Multimodality Adaptive Control

Randa Herzallah, David Lowe

Research output: Contribution to journalArticle

Abstract

This paper develops a probabilistic multimodal adaptive control approach for systems that are characterised by temporal multimodality where the system dynamics are subject to abrupt mode switching at arbitrary times. In this framework, the control objective is redefined such that it utilises the complete probability distribution of the system dynamics. The derived probabilistic control law is thus of a dual type that incorporates the functional uncertainty of the controlled system. A multi-modal density model with prediction error-dependent mixing coefficients is introduced to effect the mode switching. This approach can deal with arbitrary noise distributions, nonlinear plant dynamics and arbitrary mode switching. For the affine systems focussed upon for illustration in this paper the approach has global stability. The theoretical architecture constructs are verified by validation on a simulation example.
Original languageEnglish
JournalInternational Journal of Control
Early online date24 Sep 2018
DOIs
Publication statusE-pub ahead of print - 24 Sep 2018

Bibliographical note

This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Control on 24 September 2018, available online at: http://www.tandfonline.com/10.1080/00207179.2018.1523567

Fingerprint Dive into the research topics of 'Probabilistic Multimodality Adaptive Control'. Together they form a unique fingerprint.

  • Cite this