Simulated neurocontrol of an autogenous mill with evolutionary reinforcement learning

Date
2007
Authors
De Groenewald J.W.V.
Aldrich C.
Eksteen J.J.
Conradie A.V.E.
Coetzer L.P.
Journal Title
Journal ISSN
Volume Title
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Abstract
In this investigation the development of nonlinear control system for an autogenous mill was considered. A symbiotic adaptive neuroevolution algorithm was used in conjunction with a dynamic multilayer perceptron model fitted to actual plant data to evolve neurocontrol systems. Simulation studies established the potential of the approach, which yielded satisfactory results, despite having had to learn from a model that covered part of the state space only. Copyright © 2007 IFAC.
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Citation
IFAC Proceedings Volumes (IFAC-PapersOnline)
7
PART 1
http://www.scopus.com/inward/record.url?eid=2-s2.0-79960955471&partnerID=40&md5=9a5a6400e60efdb179753d8d698eb950
URI
http://hdl.handle.net/10019.1/17103
Collections
Stellenbosch University - Scopus Publications