PMAC:Probabilistic Multimodality Adaptive Control


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Mathematics
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: 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:
Publication ISSN: 1366-5820
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Related URLs: https://www.tan ... 79.2018.1523567 (Publisher URL)
PURE Output Type: Article
Published Date: 2020-07-02
Published Online Date: 2018-09-24
Accepted Date: 2018-09-09
Authors: Herzallah, Randa (ORCID Profile 0000-0001-9128-6814)
Lowe, David



Version: Accepted Version

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