Probabilistic Multimodality Adaptive Control

Herzallah, Randa and Lowe, David (2018). Probabilistic Multimodality Adaptive Control. International Journal of Control ,

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.

Publication DOI: https://doi.org/10.1080/00207179.2018.1523567
Divisions: Engineering & Applied Sciences > Mathematics
Engineering & Applied 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: http://www.tandfonline.com/10.1080/00207179.2018.1523567
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Related URLs: https://www.tan ... 79.2018.1523567 (Publisher URL)
Published Online Date: 2018-09-24
Authors: Herzallah, Randa ( 0000-0001-9128-6814)
Lowe, David

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Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 24 September 2019.


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