A Multi-Parametric Method for Active Model Discrimination of Nonlinear Systems with Temporal Logic-Constrained Switching

Ruochen Niu, Syed M. Hassaan, Sze Zheng Yong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we consider the optimal input design problem for active model discrimination (AMD) among a set of switched nonlinear models that are constrained by metric/signal temporal logic specifications and affected by uncontrolled inputs and noise. To deal with nonlinear and non-convex constraints in the resulting bilevel optimization problem, we first over-approximate the nonlinear dynamics using piecewise affine abstractions. Then, we solve the relaxed inner problem of the bilevel AMD problem as parametric optimization problems and substitute the parametric solutions into the outer problem to obtain sufficient separating inputs for AMD. Moreover, since the parametric optimization problems are often computationally demanding, we propose several strategies to reduce the computational time, while preserving feasibility of the separating inputs for AMD. Finally, we demonstrate the effectiveness of our approach on several illustrative examples on fault detection and lane changing scenario.

Original languageEnglish (US)
Title of host publication2022 American Control Conference, ACC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1652-1658
Number of pages7
ISBN (Electronic)9781665451963
DOIs
StatePublished - 2022
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: Jun 8 2022Jun 10 2022

Publication series

NameProceedings of the American Control Conference
Volume2022-June
ISSN (Print)0743-1619

Conference

Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States
CityAtlanta
Period6/8/226/10/22

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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