PMAC: Probabilistic Multimodality Adaptive Control

Randa Herzallah, David Lowe

Research output: Contribution to journalArticlepeer-review


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
Pages (from-to)1637-1650
Number of pages14
JournalInternational Journal of Control
Issue number7
Early online date24 Sep 2018
Publication statusPublished - 2 Jul 2020

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:


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