Incremental Stability and Performance Analysis of Discrete-Time Nonlinear Systems using the LPV Framework

Patrick J.W. Koelewijn (Corresponding author), Roland Toth (Corresponding author)

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)
60 Downloads (Pure)

Abstract

The dissipativity framework is widely used to analyze stability and performance of nonlinear systems. By embedding nonlinear systems in an LPV representation, the convex tools of the LPV framework can be applied to nonlinear systems for convex dissipativity based analysis and controller synthesis. However, as has been shown recently in literature, naive application of these tools to nonlinear systems for analysis and controller synthesis can fail to provide the desired guarantees. Namely, only performance and stability with respect to the origin is guaranteed. In this paper, inspired by the results for continuous-time nonlinear systems, the notion of incremental dissipativity for discrete-time nonlinear systems is proposed, whereby stability and performance analysis is done between trajectories. Furthermore, it is shown how, through the use of the LPV framework, convex conditions can be obtained for incremental dissipativity analysis of discrete-time nonlinear systems. The developed concepts and tools are demonstrated by analyzing incremental dissipativity of a controlled unbalanced disk system.

Original languageEnglish
Pages (from-to)75-82
Number of pages8
JournalIFAC-PapersOnLine
Volume54
Issue number8
DOIs
Publication statusPublished - 1 Jul 2021
Event4th IFAC Workshop on Linear Parameter Varying Systems, LPVS 2021 - Milan, Italy
Duration: 19 Jul 202120 Jul 2021

Bibliographical note

Publisher Copyright:
Copyright © 2021 The Authors. This is an open access article under the CC BY-NC-ND license.

Funding

FundersFunder number
European Union's Horizon 2020 - Research and Innovation Framework Programme714663

    Keywords

    • Discrete-time systems
    • Incremental dissipativity
    • Nonlinear systems
    • Stability and stabilization

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