Generalised Absolute Stability and Sum of Squares

This paper introduces a general framework for analysing systems that have non-polynomial, uncertain or high order nonlinearities. It decomposes the vector field using Lur'e type feedback into a system with a polynomial or rational vector field and a nonlinear memoryless feedback term, which is...

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Main Authors: Hancock, E, Papachristodoulou, A, IEEE
Format: Conference item
Published: 2011
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author Hancock, E
Papachristodoulou, A
IEEE
author_facet Hancock, E
Papachristodoulou, A
IEEE
author_sort Hancock, E
collection OXFORD
description This paper introduces a general framework for analysing systems that have non-polynomial, uncertain or high order nonlinearities. It decomposes the vector field using Lur'e type feedback into a system with a polynomial or rational vector field and a nonlinear memoryless feedback term, which is bounded by polynomial or rational functions. This decomposition can be used to model uncertainty in the nonlinear term or to bound difficult to analyse nonlinearities by simpler polynomial or rational functions. Conditions for stability are found using Lyapunov functions which are generalisations of those used for the derivation of the multivariable circle and Popov criteria. These conditions can be given in terms of polynomial inequalities and so Sum of Squares techniques can be used to efficiently analyse these systems. An example shows how the techniques can be applied to uncertain coupled genetic circuits and a pendulum, where the nonlinearity is bounded by polynomial functions. The technique is also applied to show global stability of a system in which classical absolute stability is inconclusive. © 2011 AACC American Automatic Control Council.
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spelling oxford-uuid:f279751f-6444-4d98-bbf0-c459863397af2022-03-27T12:04:05ZGeneralised Absolute Stability and Sum of SquaresConference itemhttp://purl.org/coar/resource_type/c_5794uuid:f279751f-6444-4d98-bbf0-c459863397afSymplectic Elements at Oxford2011Hancock, EPapachristodoulou, AIEEEThis paper introduces a general framework for analysing systems that have non-polynomial, uncertain or high order nonlinearities. It decomposes the vector field using Lur'e type feedback into a system with a polynomial or rational vector field and a nonlinear memoryless feedback term, which is bounded by polynomial or rational functions. This decomposition can be used to model uncertainty in the nonlinear term or to bound difficult to analyse nonlinearities by simpler polynomial or rational functions. Conditions for stability are found using Lyapunov functions which are generalisations of those used for the derivation of the multivariable circle and Popov criteria. These conditions can be given in terms of polynomial inequalities and so Sum of Squares techniques can be used to efficiently analyse these systems. An example shows how the techniques can be applied to uncertain coupled genetic circuits and a pendulum, where the nonlinearity is bounded by polynomial functions. The technique is also applied to show global stability of a system in which classical absolute stability is inconclusive. © 2011 AACC American Automatic Control Council.
spellingShingle Hancock, E
Papachristodoulou, A
IEEE
Generalised Absolute Stability and Sum of Squares
title Generalised Absolute Stability and Sum of Squares
title_full Generalised Absolute Stability and Sum of Squares
title_fullStr Generalised Absolute Stability and Sum of Squares
title_full_unstemmed Generalised Absolute Stability and Sum of Squares
title_short Generalised Absolute Stability and Sum of Squares
title_sort generalised absolute stability and sum of squares
work_keys_str_mv AT hancocke generalisedabsolutestabilityandsumofsquares
AT papachristodouloua generalisedabsolutestabilityandsumofsquares
AT ieee generalisedabsolutestabilityandsumofsquares