Joint Synthesis of Trajectory and Controlled Invariant Funnel for Discrete-time Systems with Locally Lipschitz Nonlinearities
This paper presents a joint synthesis algorithm of trajectory and controlled invariant funnel (CIF) for locally Lipschitz nonlinear systems subject to bounded disturbances. The CIF synthesis refers to a procedure of computing controlled invariance sets and corresponding feedback gains. In contrast t...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
07.09.2022
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Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.2209.03535 |
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Abstract | This paper presents a joint synthesis algorithm of trajectory and controlled
invariant funnel (CIF) for locally Lipschitz nonlinear systems subject to
bounded disturbances. The CIF synthesis refers to a procedure of computing
controlled invariance sets and corresponding feedback gains. In contrast to
existing CIF synthesis methods that compute the CIF with a pre-defined nominal
trajectory, our work aims to optimize the nominal trajectory and the CIF
jointly to satisfy feasibility conditions without the relaxation of constraints
and obtain a more cost-optimal nominal trajectory. The proposed work has a
recursive scheme that mainly optimize trajectory update and funnel update. The
trajectory update step optimizes the nominal trajectory while ensuring the
feasibility of the CIF. Then, the funnel update step computes the funnel around
the nominal trajectory so that the CIF guarantees an invariance property. As a
result, with the optimized trajectory and CIF, any resulting trajectory
propagated from an initial set by the control law with the computed feedback
gain remains within the feasible region around the nominal trajectory under the
presence of bounded disturbances. We validate the proposed method via two
applications from robotics. |
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AbstractList | This paper presents a joint synthesis algorithm of trajectory and controlled
invariant funnel (CIF) for locally Lipschitz nonlinear systems subject to
bounded disturbances. The CIF synthesis refers to a procedure of computing
controlled invariance sets and corresponding feedback gains. In contrast to
existing CIF synthesis methods that compute the CIF with a pre-defined nominal
trajectory, our work aims to optimize the nominal trajectory and the CIF
jointly to satisfy feasibility conditions without the relaxation of constraints
and obtain a more cost-optimal nominal trajectory. The proposed work has a
recursive scheme that mainly optimize trajectory update and funnel update. The
trajectory update step optimizes the nominal trajectory while ensuring the
feasibility of the CIF. Then, the funnel update step computes the funnel around
the nominal trajectory so that the CIF guarantees an invariance property. As a
result, with the optimized trajectory and CIF, any resulting trajectory
propagated from an initial set by the control law with the computed feedback
gain remains within the feasible region around the nominal trajectory under the
presence of bounded disturbances. We validate the proposed method via two
applications from robotics. |
Author | Kim, Taewan Elango, Purnanand Acikmese, Behcet |
Author_xml | – sequence: 1 givenname: Taewan surname: Kim fullname: Kim, Taewan – sequence: 2 givenname: Purnanand surname: Elango fullname: Elango, Purnanand – sequence: 3 givenname: Behcet surname: Acikmese fullname: Acikmese, Behcet |
BackLink | https://doi.org/10.48550/arXiv.2209.03535$$DView paper in arXiv |
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Copyright | http://creativecommons.org/licenses/by/4.0 |
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Snippet | This paper presents a joint synthesis algorithm of trajectory and controlled
invariant funnel (CIF) for locally Lipschitz nonlinear systems subject to
bounded... |
SourceID | arxiv |
SourceType | Open Access Repository |
SubjectTerms | Mathematics - Optimization and Control |
Title | Joint Synthesis of Trajectory and Controlled Invariant Funnel for Discrete-time Systems with Locally Lipschitz Nonlinearities |
URI | https://arxiv.org/abs/2209.03535 |
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