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 Sept 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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