Convex Computation of the Region of Attraction of Polynomial Control Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00214843" target="_blank" >RIV/68407700:21230/14:00214843 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TAC.2013.2283095" target="_blank" >http://dx.doi.org/10.1109/TAC.2013.2283095</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TAC.2013.2283095" target="_blank" >10.1109/TAC.2013.2283095</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Convex Computation of the Region of Attraction of Polynomial Control Systems

Popis výsledku v původním jazyce

We address the long-standing problem of computing the region of attraction (ROA) of a target set (e.g., a neighborhood of an equilibrium point) of a controlled nonlinear system with polynomial dynamics and semialgebraic state and input constraints. We show that the ROA can be computed by solving an infinite-dimensional convex linear programming (LP) problem over the space of measures. In turn, this problem can be solved approximately via a classical converging hierarchy of convex finite- dimensional linear matrix inequalities (LMIs). Our approach is genuinely primal in the sense that convexity of the problem of computing the ROA is an outcome of optimizing directly over system trajectories. The dual infinite-dimensional LP on nonnegative continuous functions (approximated by polynomial sum-of-squares) allows us to generate a hierarchy of semialgebraic outer approximations of the ROA at the price of solving a sequence of LMI problems with asymptotically vanishing conservatism. This shar

Název v anglickém jazyce

Convex Computation of the Region of Attraction of Polynomial Control Systems

Popis výsledku anglicky

We address the long-standing problem of computing the region of attraction (ROA) of a target set (e.g., a neighborhood of an equilibrium point) of a controlled nonlinear system with polynomial dynamics and semialgebraic state and input constraints. We show that the ROA can be computed by solving an infinite-dimensional convex linear programming (LP) problem over the space of measures. In turn, this problem can be solved approximately via a classical converging hierarchy of convex finite- dimensional linear matrix inequalities (LMIs). Our approach is genuinely primal in the sense that convexity of the problem of computing the ROA is an outcome of optimizing directly over system trajectories. The dual infinite-dimensional LP on nonnegative continuous functions (approximated by polynomial sum-of-squares) allows us to generate a hierarchy of semialgebraic outer approximations of the ROA at the price of solving a sequence of LMI problems with asymptotically vanishing conservatism. This shar

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-06894S" target="_blank" >GA13-06894S: Semidefinitní programování pro polynomiální problémy optimálního řízení</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Automatic Control

ISSN

0018-9286

e-ISSN

—

Svazek periodika

59

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

297-312

Kód UT WoS článku

000330767500002

EID výsledku v databázi Scopus

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