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Implementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems.

Dentler, Jan; Kannan, Somasundar; Olivares-Mendez, Miguel A.; Voos, Holger

Authors

Jan Dentler

Miguel A. Olivares-Mendez

Holger Voos



Abstract

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs).

Citation

DENTLER, J., KANNAN, S., OLIVARES-MENDEZ, M.A. and VOOS, H. 2017. Implementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems. In Proceedings of the 1st IEEE (Institute of Electrical and Electronics Engineers) Conference on control technology and applications 2017 (CCTA 2017), 27-30 August 2017, Kohala Coast, USA. Piscataway: IEEE [online], pages 1000-1007. Available from: https://doi.org/10.1109/CCTA.2017.8062590

Conference Name 1st IEEE (Institute of Electrical and Electronics Engineers) conference on control technology and applications 2017 (CCTA 2017)
Conference Location Kohala Coast, USA
Start Date Aug 27, 2017
End Date Aug 30, 2017
Acceptance Date Jun 1, 2017
Online Publication Date Aug 30, 2017
Publication Date Oct 9, 2017
Deposit Date Oct 17, 2022
Publicly Available Date Mar 29, 2024
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 1000-1006
DOI https://doi.org/10.1109/CCTA.2017.8062590
Keywords Robots; Couplings; Optimization; Real-time systems; Predictive control; Optimal control
Public URL https://rgu-repository.worktribe.com/output/1279786
Publisher URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047728757&doi=10.1109%2fCCTA.2017.8062590&partnerID=40&md5=28be389d3ec78e41ac203cafcb2e9392

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DENTLER 2017 Implementation and validation (AAM) (1.3 Mb)
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