University of Twente Student Theses


Learning Multi-Agent Control with OROCOS

Rezola Exteberria, I. (2009) Learning Multi-Agent Control with OROCOS.

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Abstract:In previous research projects, we have used a number of different techniques / methods that are applicable in advanced control of mechatronic systems, i.e.: • Learning Feed-Forward Control; see e.g. pdf-files/Cuong_thesis.pdf, and • Multi-Agent Control Systems; see e.g. and van Breemen.pdf • OROCOS (Open Realtime Control Services and Open Robot Control Software) running on top of Xenomai/RTAI; see , and Currently, efforts are made to integrate these methods so as to obtain a suitable framework for advanced control of mechatronic systems. Specifically, we envision Multi-Agent Control Systems to become Tasks in OROCOS, and LFFC as a pattern for incorporation in a Multi-Agent Control System, with the specific property that learning is done asynchronously, in a separate non-realtime Task. Goal of the project is to evaluate the feasibility of the proposed integration. This is to be done by designing and implementing a simple Multi-Agent Control System with path generation and PID control in OROCOS and subsequently adding a Learning Feed-Forward Component that can learn on-line
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Electrical Engineering MSc (60353)
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