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

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

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 1st IEEE (Institute of Electrical and Electronics Engineers) conference on control technology and applications 2017 (CCTA 2017)
• 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: Oct 17, 2022
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• 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