Incremental Dissipativity based Control of Discrete-Time Nonlinear Systems via the LPV Framework

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Abstract

Unlike for Linear Time-Invariant (LTI) systems, for nonlinear systems, there exists no general framework for systematic convex controller design which incorporates performance shaping. The Linear Parameter-Varying (LPV) framework sought to bridge this gap by extending convex LTI synthesis results such that they could be applied to nonlinear systems. However, recent literature has shown that naive application of the LPV framework can fail to guarantee the desired asymptotic stability guarantees for nonlinear systems. Incremental dissipativity theory has been successfully used in the literature to overcome these issues for Continuous- Time (CT) systems. However, so far no solution has been proposed for output-feedback based incremental control for the Discrete-Time (DT) case. Using recent results on convex analysis of incremental dissipativity for DT nonlinear systems, in this paper, we propose a convex output-feedback controller synthesis method to ensure closed-loop incremental dissipativity of DT nonlinear systems via the LPV framework. The proposed method is applied on a simulation example, demonstrating improved stability and performance properties compared to a standard LPV controller design.
Original languageEnglish
Title of host publication60th IEEE Conference on Decision and Control (CDC 2021)
PublisherInstitute of Electrical and Electronics Engineers
Pages3281-3286
Number of pages6
ISBN (Electronic)978-1-6654-3659-5
DOIs
Publication statusPublished - 1 Feb 2022
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, TX, USA, Austin, United States
Duration: 13 Dec 202117 Dec 2021
Conference number: 60
https://2021.ieeecdc.org/

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Abbreviated titleCDC 2021
Country/TerritoryUnited States
CityAustin
Period13/12/2117/12/21
Internet address

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