Distributed learning for multi-agent control of a dynamic system

This thesis describes an investigation of self-organising, distributed control of dynamic, non-linear systems. The distribution is achieved through a multi-agent based approach. The self-organisation is addressed through reinforcement learning. The feasibility is tested using a well-established agen...

Full description

Bibliographic Details
Main Author: Pay, Mungo Louis
Other Authors: Clarke, Tim ; Tyrrell, Andrew
Published: University of York 2011
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556338
id ndltd-bl.uk-oai-ethos.bl.uk-556338
record_format oai_dc
spelling ndltd-bl.uk-oai-ethos.bl.uk-5563382017-10-04T03:18:50ZDistributed learning for multi-agent control of a dynamic systemPay, Mungo LouisClarke, Tim ; Tyrrell, Andrew2011This thesis describes an investigation of self-organising, distributed control of dynamic, non-linear systems. The distribution is achieved through a multi-agent based approach. The self-organisation is addressed through reinforcement learning. The feasibility is tested using a well-established agent framework: JADE. The target system for the study is a simulation of a well-known laboratory demonstrator, the twin-rotor MIMO system, but configured to introduce strong cross-couplings in its non-linear dynamics. A multi-agent PID controller is developed as an interim solution to test the feasibility of the use of JADE for control purposes. An overarching constraint on the development of any solutions was that the plant knowledge was minimal, which placed great importance on the need for a self-organising scheme. Results of a developed system are presented against the context of more conventional control methodologies.006.3University of Yorkhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556338http://etheses.whiterose.ac.uk/2294/Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 006.3
spellingShingle 006.3
Pay, Mungo Louis
Distributed learning for multi-agent control of a dynamic system
description This thesis describes an investigation of self-organising, distributed control of dynamic, non-linear systems. The distribution is achieved through a multi-agent based approach. The self-organisation is addressed through reinforcement learning. The feasibility is tested using a well-established agent framework: JADE. The target system for the study is a simulation of a well-known laboratory demonstrator, the twin-rotor MIMO system, but configured to introduce strong cross-couplings in its non-linear dynamics. A multi-agent PID controller is developed as an interim solution to test the feasibility of the use of JADE for control purposes. An overarching constraint on the development of any solutions was that the plant knowledge was minimal, which placed great importance on the need for a self-organising scheme. Results of a developed system are presented against the context of more conventional control methodologies.
author2 Clarke, Tim ; Tyrrell, Andrew
author_facet Clarke, Tim ; Tyrrell, Andrew
Pay, Mungo Louis
author Pay, Mungo Louis
author_sort Pay, Mungo Louis
title Distributed learning for multi-agent control of a dynamic system
title_short Distributed learning for multi-agent control of a dynamic system
title_full Distributed learning for multi-agent control of a dynamic system
title_fullStr Distributed learning for multi-agent control of a dynamic system
title_full_unstemmed Distributed learning for multi-agent control of a dynamic system
title_sort distributed learning for multi-agent control of a dynamic system
publisher University of York
publishDate 2011
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556338
work_keys_str_mv AT paymungolouis distributedlearningformultiagentcontrolofadynamicsystem
_version_ 1718543060684505088