Robust Linear Quadratic Regulator for uncertain systems

Ioannis Tzortzis, Charalambos D. Charalambous, Themistoklis Charalambous, Christos K. Kourtellaris, Christoforos N. Hadjicostis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

This paper develops a Linear Quadratic Regulator (LQR), which is robust to disturbance variability, by using the total variation distance as a metric. The robust LQR problem is formulated as a minimax optimization problem, resulting in a robust optimal controller which in addition to minimizing the quadratic cost it also minimizes the level of disturbance variability. A procedure for solving the LQR problem is also proposed and an example is presented which clearly illustrates the effectiveness of our developed methodology.

Original languageEnglish
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherIEEE
Pages1515-1520
Number of pages6
ISBN (Electronic)9781509018376
DOIs
Publication statusPublished - 27 Dec 2016
MoE publication typeA4 Article in a conference publication
EventIEEE Conference on Decision and Control - ARIA Resort & Casino, Las Vegas, United States
Duration: 12 Dec 201614 Dec 2016
Conference number: 55

Conference

ConferenceIEEE Conference on Decision and Control
Abbreviated titleCDC
CountryUnited States
CityLas Vegas
Period12/12/201614/12/2016

Fingerprint Dive into the research topics of 'Robust Linear Quadratic Regulator for uncertain systems'. Together they form a unique fingerprint.

Cite this