Robust synthesis for linear parameter varying systems using integral quadratic constraints

Shu Wang, Harald Pfifer, Peter J Seiler Jr

Research output: Contribution to journalConference article

6 Citations (Scopus)

Abstract

A robust synthesis algorithm is proposed for a class of uncertain linear parameter varying (LPV) systems. The uncertain system is described as an interconnection of a nominal (not-uncertain) LPV system and an uncertainty whose input/output behavior is described by an integral quadratic constraint (IQC). The proposed algorithm is a coordinate-wise ascent that is similar to the well-known DK iteration for μ-synthesis. In the first step, a nominal controller is designed for the LPV system without uncertainties. In the second step, the robustness of the designed controller is evaluated and a new scaled plant for the next synthesis step is created. The robust performance condition used in the analysis step is formulated as a dissipation inequality that incorporates the IQC and generalizes the Bounded Real Lemma like condition for performance of nominal LPV systems. Both steps can be formulated as a semidefinite program (SDP) and efficiently solved using available optimization software. The effectiveness of the proposed method is demonstrated on a simple numerical example.

Original languageEnglish (US)
Article number7040136
Pages (from-to)4789-4794
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2015-February
Issue numberFebruary
DOIs
StatePublished - Jan 1 2014
Event2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States
Duration: Dec 15 2014Dec 17 2014

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Linear Parameter-varying Systems
Quadratic Constraint
Synthesis
Categorical or nominal
Controllers
Uncertain systems
Robustness (control systems)
Controller
Uncertainty
Semidefinite Program
Robust Performance
Ascent
Uncertain Systems
Interconnection
Dissipation
Lemma
Robustness
Iteration
Numerical Examples
Generalise

Cite this

Robust synthesis for linear parameter varying systems using integral quadratic constraints. / Wang, Shu; Pfifer, Harald; Seiler Jr, Peter J.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 2015-February, No. February, 7040136, 01.01.2014, p. 4789-4794.

Research output: Contribution to journalConference article

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