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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

H-2 control and filtering of discrete-time LPV systems exploring statistical information of the time-varying parameters

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Author(s):
Palma, Jonathan M. [1, 2] ; Morais, Cecilia F. [3, 1] ; Oliveira, Ricardo C. L. F. [1]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Sch Elect & Comp Engn, UNICAMP, BR-13083852 Campinas, SP - Brazil
[2] Univ Catolica Maule UCM Talca, Fac Ciencias Ingn, Dept Comp & Ind, Talca - Chile
[3] Pontifical Catholic Univ Campinas, Ctr Exact Environm & Technol Sci, BR-13086900 Campinas, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS; v. 357, n. 6, p. 3835-3864, APR 2020.
Web of Science Citations: 0
Abstract

This paper introduces a new strategy to improve performance in gain-scheduled control and filtering for LPV systems exploiting statistical information about the time-varying parameters whenever available. The novelty of the technique, named sub-domain optimization heuristic (SDOH), is to design controllers or filters treating robust stability independently of performance. The performance is optimized only in a sub-domain of the time-varying parameters, where a higher frequency of occurrence is expected, while the robust stability is certificated for the whole domain. The problem of gain-scheduled design subject to inexact measurements is discussed in details as main motivation but any other feedback or filter strategy for LPV systems were statistical information about the time-varying parameters is known can be handled in a similar way. Still in the context of inexact measurements, a more complete modeling for the additive uncertainty is given, generalizing previous results from the literature for two types of uncertainties, polytopic and affine. A new design condition for H-2 full-order LPV filtering is also given as contribution. Several numerical examples are presented to illustrate the results. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 17/18785-5 - Parameter-Dependent Linear Matrix Inequalities Applied to Stability Analysis and Synthesis of Controllers and Filters for Uncertain Dynamic Systems
Grantee:Pedro Luis Dias Peres
Support Opportunities: Regular Research Grants