Online Tuned Model Predictive Control for Robotic Systems with Bounded Noise

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00477603" target="_blank" >RIV/67985556:_____/17:00477603 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/MMAR.2017.8046912" target="_blank" >http://dx.doi.org/10.1109/MMAR.2017.8046912</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MMAR.2017.8046912" target="_blank" >10.1109/MMAR.2017.8046912</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Online Tuned Model Predictive Control for Robotic Systems with Bounded Noise

Popis výsledku v původním jazyce

This paper deals with a discrete predictive control design for motion control of robotic systems. The design considers time-varying state-space robot model. It is assumed that used robot state has to be estimated from measured robot outputs. These outputs represent controlled quantities including a bounded noise. Considering this arrangement, the paper introduces a novel solution to the state and noise parameter estimations based on linear programming that is incorporated in the control design. Estimated states are utilised for updating state-dependent elements in the robot model and for control design itself. Estimated noise parameters are employed in advanced tuning of control parameters, namely penalisation matrices. The proposed theoretical outcomes are demonstrated on one multi-input multi-output robot-manipulator as a specific representative of robotic systems.

Název v anglickém jazyce

Online Tuned Model Predictive Control for Robotic Systems with Bounded Noise

Popis výsledku anglicky

This paper deals with a discrete predictive control design for motion control of robotic systems. The design considers time-varying state-space robot model. It is assumed that used robot state has to be estimated from measured robot outputs. These outputs represent controlled quantities including a bounded noise. Considering this arrangement, the paper introduces a novel solution to the state and noise parameter estimations based on linear programming that is incorporated in the control design. Estimated states are utilised for updating state-dependent elements in the robot model and for control design itself. Estimated noise parameters are employed in advanced tuning of control parameters, namely penalisation matrices. The proposed theoretical outcomes are demonstrated on one multi-input multi-output robot-manipulator as a specific representative of robotic systems.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 22nd IEEE International Conference on Methods and Models in Automation and Robotics

ISBN

978-1-5386-2403-6

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

694-699

Název nakladatele

West Pomeranian University of Technology

Místo vydání

Szczecin

Místo konání akce

Miedzyzdroje

Datum konání akce

28. 8. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000425229300125